Blog

  • How to deploy individual components of your Salesforce Digital Experience

    Claudia McPhail & Ahtif Anwar on October 22nd 2021

    Many teams now use Digital Experiences, Salesforce's powerful platform for building sites, apps, and portals on Experience Cloud. While creating and customizing sites has never been easier, Digital Experiences can be difficult to deploy. But help is on hand! Gearset's intelligent comparison and deployment engine not only provides an easy way to deploy your Salesforce metadata, it's the only solution that enables you to publish individual components of your Digital Experience, such as single pages or branding updates.

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  • An easier way to deploy Salesforce CPQ data

    Simon Breslaw on September 17th 2021

    Gearset's intelligent data deployment tools show you the connections within your data model, so you can easily select and deploy changes to your org's data along with all the necessary dependencies, such as parent-child relationships and circular references. This makes updating and migrating CPQ (Configure, Price, Quote) records and configuration much easier than using Salesforce's Data Loader. While Gearset already lets you save and share your own custom data deployment templates, we've recently added a default CPQ template to streamline your CPQ deployments, helping you to save time and avoid data deployment headaches.

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  • How to set up a CI job and use GitHub with Vlocity in Gearset

    Tom Smith on August 31st 2021

    As we announced in a previous post, Gearset now allows you to deploy Vlocity DataPacks alongside Salesforce metadata. The benefits over the Vlocity Build tools are clear: you can run all deployments using a single tool so your deployment history and audit trail are in one place. While you can deploy your Vlocity DataPacks with the Vlocity Build and IDX Workbench tools, managing all of your deployments using the same Salesforce DevOps solution gives you a truly agile process. Now, you can also use Gearset to include Vlocity DataPacks in your DevOps process, with version control and continuous integration.

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  • The safe way to declutter your org and make destructive changes

    Mareya Saba on August 17th 2021

    Salesforce makes it easy for you to add fields, objects and customizations. Salesforce teams don't always anticipate the problem of redundant metadata, which can quickly clutter up your org as processes evolve and plans change. Obsolete features in your org are a problem, and the solution must be carefully chosen. In this post we'll explore the reasons for deleting metadata, and how to do it safely.

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  • What is a Bot User error and how does Gearset fix it?

    Jan Letovanec on August 13th 2021

    Gearset helps make sure your deployments succeed on your first attempt. We do this by running the deployment through more than 60 problem analyzers that check for and resolve common deployment issues for you. Our problem analyzers do a lot of useful work to make sure the average deployment success rate for our users remains above 90% by fixing these issues.

    One such issue the problem analyzers look for is the Bot User error. This error relates to deploying Einstein bots, and was flagged up to us by a user.

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  • Automatic unit test selection for Salesforce deployments

    Calvin Childs on July 29th 2021

    Salesforce deployments with Gearset can be up to 12x faster than with first-party tools, and we're constantly making even more improvements to streamline your deployments and save even more of your time and effort. Currently, we're piloting new functionality that automatically suggests which unit tests you should run when you manually deploy or validate a package in Gearset. This improvement will make test selection and testing quicker and easier. It should also save lots of teams from needing to track their unit tests outside of Gearset.

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  • Salesforce deployments that just work

    Simon Breslaw on July 13th 2021

    Without the right tooling, Salesforce deployments can absorb an enormous amount of your Salesforce team's time. How do you make sure your deployments are successful on an everyday, regular and reliable basis? With its deep understanding of Salesforce metadata, Gearset is the most powerful comparison and deployment engine in the ecosystem. This post highlights the intelligent ways Gearset boosts deployment success and takes the pain and risk out of deploying on Salesforce.

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  • Easily deploy Vlocity items alongside Salesforce metadata

    Tom Smith on July 8th 2021

    Gearset now supports Vlocity deployments with new purpose-built tooling! Vlocity packages are becoming increasingly popular as a way to extend Salesforce quickly with sector-specific solutions. Before our new release, deploying Vlocity meant you had to use a dedicated deployment tool and a separate workflow to your normal Salesforce deployments - not an ideal solution. The beauty of Gearset's new Vlocity deployment tool is that you can deploy your Vlocity items alongside Salesforce metadata.

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  • Looking ahead with Gearset's product roadmap

    Ben Assirati on March 26th 2021

    Over the years, Gearset has grown alongside our users, matching ambition with precision to provide the best possible DevOps solution for Salesforce. We've navigated our way to become the leading DevOps solution by holding firm to two of our core values: listening to our community, and bringing DevOps best practices to Salesforce.

    Gearset thrives at the intersection of these values; always listening to our users and always sharing the progress we're making together. This is why we provide a platform for feature requests and suggestions, publish our roadmap, and even share the stats about how Gearset is being used around the world.

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  • Gearset's metadata filter just got even better

    Ben Scabbia on March 4th 2021

    In a recent release, we introduced more granularity to Gearset's metadata filter - as eagle-eyed users might have noticed in our change log. Many of the improvements we make to Gearset start out as user requests on our feedback forum, and several users had asked us for the ability to select subcomponents in the metadata filter. In this post I'll explain the use case for filtering out subcomponents from a comparison, so you can get the most out of Gearset's metadata filter.

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  • How to set a retention policy for Salesforce backups

    Catherine Bacon & David Runciman on February 17th 2021

    When you're setting up a backup job in Gearset, you can select a retention policy. If you're not sure exactly how long you should keep backup data for, don't worry - this is quite common. In this post, we'll explain how retention policies work and what you normally need to think about when setting a retention period. Make sure you also talk to your company's compliance and data protection officers - retention policies usually fall within their remit.

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  • View your Apex code coverage line by line in Gearset

    Sam Williams on February 12th 2021

    An important principle of software development is making sure your tests dig into all the deepest recesses of your code. After all, a mistake could creep into any line - and if a bug only gets triggered by an edge case, it won't surface for a long time. When it finally does emerge, it'll be harder to fix because you won't remember that part of your codebase.

    We've recently released a new feature that lets you view your code coverage not just class by class, but also line by line.

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  • Your Salesforce org gets corrupted - who you gonna call?

    Alex Walter on February 10th 2021

    Imagine this nightmare scenario. It's late Friday afternoon when you get an urgent message from the team: your company's data has been corrupted by a rogue Apex class. It's scramble time! You need to use your backups to restore your Salesforce accounts - and you need them restored by the start of play on Monday. But the team member responsible for setting up and managing your backups is on a week-long vacation. Everyone's counting on you.

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  • Managing Salesforce teams in Gearset

    Simon Breslaw on September 21st 2020

    To get the most out of your Salesforce investment, it helps to give everyone on your Salesforce team the freedom to get on with their work by allowing them to continually build, test and ship to production. Giving everyone access to the DevOps tools and resources they need to collaborate effectively breaks down silos and makes it possible for administrators and developers to get added value into the hands of your end users regularly, reliably and as quickly as possible without the risk of breaking something.

    As Salesforce is at the heart of your business, you'll want to safeguard your production orgs while, at the same time, empowering every member of your team to the greatest extent possible. Gearset simplifies, streamlines and hugely speeds up the development and release process for everyone, regardless of their job role and responsibilities. This post gives you a high-level overview of the flexible team management options across all of Gearset's features.

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  • How Gearset can help ISVs with first-generation packages

    Eric Kintzer on August 27th 2020

    This how-to guide for ISVs is contributed by the awesome Eric Kintzer, Salesforce Architect at Helix, and Gearset Community Advisor.

    If you're an ISV with a first-generation managed package, you can use Gearset to improve your DevOps flow. This is true whether or not you use version control. In this post, I'll describe what the developer workflow usually looks like without Gearset, and then explain how to set up a better workflow with Gearset.

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  • Introducing high-frequency backups (pilot)

    David Emmerson on August 21st 2020

    We recognize that some of your Salesforce objects get modified frequently because they're affected by a large number of changes every day. For these circumstances, we're extending Gearset's current backup offering with an option for high-frequency backups.

    This new feature is now available to all backup users for free during our pilot phase, so that everyone can try it out and determine if it fits their use cases. We'd love you to give high-frequency backups a try and let us know what you think!

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  • Making Salesforce data deployments more successful

    Tom Smith on July 20th 2020

    Gearset is always looking into different ways we can improve our users' deployment success rate. We noticed recently that some of our users were hitting particular Salesforce errors when deploying large numbers of records, so we tuned up Gearset to make your data deployments more likely to succeed first time. In this post, we'll look at what causes those errors and explain how we've gone about solving the problem for you.

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  • Faster metadata comparisons for large Salesforce orgs

    Gwilym Kuiper on June 18th 2020

    One of Gearset's core functions (that our users love 🤩 ) is to give you full insight into all of the changes you and your team have made to your Salesforce environments. With its line-by-line diff viewer showing granular detail, Gearset's comparison tooling helps you to understand exactly what's changed in your source environment compared to your deployment target.

    Gearset is able to show you the exact differences and current status of your orgs by retrieving your metadata from the Salesforce Metadata API. To boost retrieval times from the API, particularly for larger orgs, we've developed a smart new workflow under Gearset's hood that makes use of cached comparisons you've run against the same org in the past. If you're comparing new changes against a big old Salesforce org, our metadata retrievals based on cached comparisons should now save you lots of time.

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  • What is 'flowAccesses' and why's it suddenly showing up in my Salesforce metadata?

    Valerio Chang on June 9th 2020

    Recently, a new item of Salesforce metadata started showing up unexpectedly in Gearset org comparisons and monitoring jobs. Some of Gearset's users spotted flowAccesses in their Profile metadata, and asked us about this mystery metadata.

    We help users to solve their problems every day, so we're good at getting to the bottom of these kinds of puzzles. But this was an especially interesting puzzle because flowAccesses isn't listed among the other items of Profile metadata in Salesforce's metadata API developer guide. In fact, as of yet, there's no Salesforce documentation anywhere on flowAccesses.

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  • What Salesforce data do I need to back up?

    David Runciman on June 2nd 2020

    If you've been following our posts on backup for Salesforce, you'll appreciate how important it is to back up both your data and metadata. But does that mean you should back up absolutely everything in your org? Although this might seem a good idea, it's not necessary. In fact, backing up the data from every object in your org can have a negative impact on your backup and restore process. In this post, we'll explore how to choose which objects you should back up.

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  • Trouble understanding your Salesforce deployment packages?

    Ben Roberts on April 30th 2020

    Whenever you deploy with Gearset, more than fifty problem analyzers automatically check your deployment package, catching common causes of deployment failure and suggesting how you can fix them before you deploy. This saves you from having to work out what went wrong with your deployment after it failed, or deploying changes to source control that won't be deployable to a Salesforce environment.

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  • Track your team's progress with release management reporting for Salesforce

    Matt Guy on March 9th 2020

    No team of Salesforce developers and admins wants to waste unnecessary time and effort on releases. Less time spent on deployments means more time building new features. Fewer deployment failures mean more frequent releases.

    If you're already using Gearset, then you know from experience how much time and effort you've saved. But by how much has your release cadence increased? Are your deployments getting more reliable? Is your team still improving? We've added a new Reporting page to Gearset, so that you can track your team's progress.

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  • Gearset's repo dependency cleaner - keep your metadata deployable

    Jonathan Plumridge on February 14th 2020

    Gearset has always championed the use of source control within Salesforce DevOps. We make it easy for teams to build a release process around source control, and it's been great to see more and more teams reaping the rewards of doing just that. What's more, we also help you to overcome potential difficulties that come from using a version control system (VCS). Gearset's repo dependency cleaner fixes one such difficulty: metadata in a Git repo becoming undeployable.

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  • 'Duplicate picklist value' deployment error for 'AddressStateCode'

    Valerio Chang on January 7th 2020

    At Gearset, our dedicated Customer Success team is always on hand to help you out if you ever get stuck. Just alert us to the problem in our in-app chat, and we'll take a look. More often than not, we'll have come across the issue before, or else our friendly developers will jump in with their wealth of experience to sort the difficulty out with you. But every now and then, one of our users will stumble upon an error in the Salesforce Metadata API that we're powerless to fix. A good example is the bug that causes Salesforce to raise the Duplicate picklist value specified:AG deployment error.

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  • Understanding your Salesforce org comparison in Gearset - an Architect's perspective

    Marc Behr on November 11th 2019

    Today's post is brought to you by Marc Behr, Salesforce Solutions Architect, Dreamforce speaker and one of Gearset's Community Advisors.

    Before deploying changes between Salesforce environments, it's really important you understand the shape of your source and target. By being able to see how they compare, and how they differ, you're in a much stronger position to build deployment packages that will keep your orgs in sync. This is why a comparison is always the first step in your deployment process with Gearset.

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  • Redeploy packages to a new target with Gearset

    Jess Wilkinson on October 29th 2019

    As those of you familiar with Gearset are likely aware, most things in Gearset start with a comparison. Gearset takes the metadata for two orgs and runs a comparison between them, which has lots of benefits. Comparisons underpin many of Gearset’s useful features, like the ability to decompose and recompose complex metadata types to avoid conflicts, perform sophisticated dependency analysis and highlight when you might be about to overwrite something by mistake.

    Comparisons let you build deployments in Gearset painlessly. But what if you need to ship the same changes to multiple environments? If you’re running a lot of comparisons, waiting for them to finish can slow your process down. Combine this with the need to monitor subsequent stages of Gearset’s workflow, such as manually selecting components to deploy and running problem analysers, and it quickly gets time-consuming to rebuild deployment packages. Fortunately, there’s good news: Gearset now lets you deploy the same package to a new target org without initiating a new comparison or repeating the analysis steps.

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  • How to set up automatic validations of pull requests for orgs in a CI workflow

    Jess Wilkinson on October 7th 2019

    At Gearset, we’re always listening to our users. From feature requests to pain points, your feedback shapes what we build. Recently, we heard from Salesforce teams using the feature branch model about some changes we could make to improve the way Gearset handles CI jobs across multiple feature branches. In light of this feedback, we’ve added automatic pull request validations to Gearset’s continuous integration feature.

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  • A guide to diagnosing CI job failures

    Eric Kintzer on August 26th 2019

    Today’s post is brought to you by the wonderful Eric Kintzer, Salesforce Architect and one of Gearset’s Community Advisors.

    A common use of Gearset is to run Continuous Integration (CI) jobs between your source control and a reference org (let's say, the CI org) to check that your changes:

    • Are deployable (with no missing components)
    • Don't break regression tests

    Gearset runs a comparison between the source branch and the CI org (no different than any other comparison) and then deploys the changed metadata and runs the tests specified in the CI job setup. CI jobs can be validation-only or full-on deploys.

    If you get errors, the View History button on the CI job run lets you see what went wrong to help you fix any issues just like any normal deployment.

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  • Track Apex code quality with informative visuals

    Matt Guy on August 15th 2019

    Static code analysis (SCA) is a method developers use to detect errors and issues with their code - in our case, Apex. While nobody's opposed to improving the quality of their code, too often SCA tools generate long lists of code violation warnings that make it difficult for teams to focus on areas to improve, or even know what to start with!

    Gearset's SCA feature already helps users to focus on specific problem areas in their codebase by allowing them to customize the rulesets that determine how code violations are displayed. We think it's much easier to start with the ruleset that matters most to you, and to track violations of important rules before expanding your ruleset once you get those violations under control. So we've added some user-friendly visualization to help you get a better overview of the quality of your code and track trends over time.

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  • Create pull requests in Bitbucket from Gearset's UI

    Catherine Bacon on August 7th 2019

    Back in January this year, we made it possible for users with GitHub accounts to create pull requests in GitHub without leaving Gearset's user interface. Now we know plenty of folks who prefer Bitbucket for version control - often it's because of the platform's tight integration with Jira. But, whatever your preference, Gearset plays nice with all major Git platforms! So, really, it was just a matter of time before the requests for the same functionality for Bitbucket were coming in thick and fast, too.

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  • Updates on Jira integration

    Gabriel Cowley on June 26th 2019

    Gearset's integration with Jira has been around for a while now and has made it easier for users to automatically track the progress of user stories. Since its initial release, it has evolved in response to the helpful user feedback we've received. This article outlines some of the improvements that we've made over the past several months to Gearset's Jira integration.

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  • Introducing Salesforce data masking in Gearset

    Tom Smith on June 25th 2019

    Using realistic data for testing is a great way to find bugs earlier in your CI pipeline. The best data that you'll ever be able to use for testing is your production data. It contains the intricacies that your code needs to deal with. However, regulations and controls restrict access to sensitive information stored in production. In the past, this might have prevented you from using production data for testing.

    The good news is that Gearset now supports data masking during data deployments. Data masking obfuscates sensitive information while maintaining the complex relationships within your data.

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  • SSH support for custom git connections

    Gabriel Cowley on April 26th 2019

    For quite a while now, Gearset has supported integration with source control platforms via OAuth or via a custom git connection that uses a username and password to authenticate via HTTPS. You can find more details on this feature here. While the existing feature covered most of the required scenarios for integrating your git repositories with Gearset, some of our users requested SSH support for custom git connections. We're therefore pleased to announce that the latest release of Gearset supports SSH for custom git connections. Below are a few simple instructions on how to set up an SSH-based custom git connection.

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  • GitHub build statuses for your Gearset CI jobs

    Gabriel Cowley on April 24th 2019

    As an admin or developer, when you’re making changes to a Salesforce environment and pushing them to a branch in GitHub, you’ll want to regularly check that these changes are actually building and deployable. Until recently, the best way to do that would be setting up a CI job to monitor your branch and push any changes to a sandbox environment, where you’d be able to see whether they’re deployable and working as expected. While this technique works well, it means you have to actively keep a close eye on the CI jobs page, which could be easy to forget about in our busy schedules.

    One of our latest features ties your CI job back to your branch in GitHub: with each commit you'll be able to see a build status in GitHub, so you can see on the branch itself whether the job is succeeding, and whether your changes are deployable. Commit-by-commit build statuses means that if your CI job does start to fail, you’ll notice much quicker and be able to see exactly which commit caused the problem. This helps you get to the root of the issue faster, and fix it right away.

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  • Smart data deployment filters

    Alex Walter on April 23rd 2019

    Gearset's data loader is an incredibly effective way to deploy data from one org to another, whether for sandbox seeding, debugging, or just general day-to-day feature development. That said, until recently, its ability to narrow down to a specific subset of interesting records was fairly limited.

    In a recent release, we've made some changes to make it much easier to define the specific set of records you want to deploy. By applying logical operators, such as a multi-value OR, an is empty or an is not empty operator, you can include all the records you need in a single deployment, rather than having to do multiple deployments between the same two orgs. Similarly, you might want to use a greater than or a less than operator to include all the records created or modified before or after a particular date and time.

    Object filter settings
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  • Why is my CI deployment taking longer than expected?

    Eric Kintzer on April 1st 2019

    Today’s post is brought to you by our good friend Eric Kintzer, Salesforce Architect and one of Gearset’s Community Advisors.

    Assumption: you’ve configured an automatic deployment from source control to your continuous integration (CI) org.

    When deploying in this situation, the developer wants the deployment to run as quickly as possible. When it does not, the developer's workflow is interrupted and, if not addressed, results in repeated frustration every time one commits to master (such as after a code review of a pull request).

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  • Attach Azure DevOps work items to your Salesforce deployments

    Calvin Childs on April 1st 2019

    At Gearset, we want to make it as easy as possible for you to build the release process that works best for you. This means making sure you have everything you need in one place - integrating with your favourite tools to ensure your process is streamlined and simple.

    Continuing on this mission, we’ve added a new work tracking feature for anyone that uses Azure DevOps (formerly known as VSTS) instead of Jira. Our new integration with Azure DevOps boards within your Gearset deployment process lets you attach and automatically update your Azure work items when you deploy, without having to leave the app.

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  • An introduction to deploying changes to Salesforce CPQ

    Tom Smith on February 11th 2019

    Salesforce CPQ & Billing (CPQ) is a popular package from the AppExchange. It helps your sales team create fast, accurate and professional quotes.

    CPQ stands for Configure Price Quote. If you're unfamiliar with CPQ, there are plenty of resources to help you find out more, but to summarize, with CPQ a sales rep can:

    • Configure the combination of products and services which suit the customer.
    • Adjust the price to handle volume pricing or special discounts.
    • Create and send a quote to the customer.

    Unlike many other packages, CPQ configuration is stored as data, so migrating changes to CPQ between environments involves data rather than metadata deployments.

    In the rest of this post, we'll look at how to deploy CPQ changes with Gearset.

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  • GitHub users can now create a pull request from a feature branch, without having to leave Gearset

    Calvin Childs on January 29th 2019

    When working with source control orgs in Gearset, it’s common to adopt a typical Git workflow for feature development and bug fixes. When work starts on a new work item, a developer or admin would create a feature branch, then iteratively make their changes and test until the feature or fix is ready, at which point the feature branch would be merged into the release version of the app via a pull request. In the latest release of Gearset, GitHub users can now create a pull request from a feature branch in just a few clicks, without having to use the GitHub UI.

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  • Repeatable data deployments with data deployment templates in Gearset

    Tom Smith on December 4th 2018

    With Gearset's data loader you can deploy test data between your orgs. That testing becomes much more effective when you're confident about what data you're using for your tests.

    Our new data deployment templates let you save and re-use the configuration after a data deployment. Re-using a configuration lets you perform repeatable data deployments, so you can be sure of the data that you're testing with.

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  • Updates to the problem analysis results page

    Catherine Bacon on November 20th 2018

    One of Gearset's core strengths is its understanding of your metadata. If you've used Gearset before, you'll have no doubt encountered one of our problem analyzers when deploying changes, offering to fix up a deployment package to help your deployment run successfully first time. In the latest release, we've made some changes to the problem analysis results to reduce clutter and improve the wording, making it more clear what changes each problem analyzer will make to your deployment package.

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  • Managed packages, v43, and activateRSS

    Alex Walter on November 13th 2018

    With summer '18, Salesforce introduced a potential bug with the way managed packages are retrieved and deployed via the metadata API. If you've seen the error Required field is missing: activateRSS when deploying the InstalledPackage type via the metadata API, then this article is for you.

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  • How to deploy flows in v44

    Catherine Bacon on November 9th 2018

    In the Winter '19 release (v44 of the metadata API), Salesforce made several changes to how flows work. There are some important changes to how this type of metadata should be deployed - read on to find out more about working with them in the latest release.

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  • Deploy your data to Salesforce production orgs

    Tom Smith on November 7th 2018

    When we first launched our Salesforce data loader, you could migrate records between Salesforce environments for testing purposes only. We didn’t allow you to deploy data to production orgs so as to help you avoid overwriting your production data by mistake. This being said, as a Salesforce admin there are a number of cases where you'll need to deploy data to your production orgs, like when you’re implementing Salesforce CPQ.

    To help our customers in these use cases, we’ve now added the ability to deploy data to your production environments. But to help you avoid mistakes and ensure you deploy cautiously, we’ve added additional warnings as there is no deployment rollback for data deployments - we won’t be able to recover any data lost!

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  • Deployment notes are now automatically copied across when cloning or combining packages

    Ellis Toms on September 19th 2018

    Deployment notes, alongside your deployment report, make it simple to see not only what changes were made to your Salesforce orgs, but why changes were made. Either compulsory or optional, deployment notes are essential for tracking every deployment your team makes, as well as ensuring your team can understand the reason behind them.

    To make sure your team can easily keep providing the essential context of their Salesforce deployments, Gearset now copies across any deployment notes when you clone or combine deployment packages, so you don’t have to!

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  • Combine multiple deployments into one single deployment package

    Ellis Toms on August 16th 2018

    Long ago, we waved goodbye to the pain of converting inbound change sets to outbound change sets with Gearset’s clone package feature. With a click of a button, you could promote successful changes to the next environment in your release pipeline. While this was, and still is, a huge time-saver, if you wanted to migrate changes from multiple deployments, you’d have to clone each in turn, or start from scratch with a fresh comparison.

    To do away with this repetition and speed up your release cycle, Gearset now lets you combine multiple deployments into a single package.

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  • Create fully configured SFDX scratch orgs from existing definition files

    Ellis Toms on July 31st 2018

    In the age of Salesforce DX, the way we build on the Salesforce platform is changing. Part of that change includes the welcoming of scratch orgs into our development process. Scratch orgs are one of the most exciting features to come out of SFDX; they’re clean, ephemeral environments that you can spin up to build packages and test deployments ahead of time, without the worry of maintaining the environment.

    Dedicated to bringing the benefits of DX to admins as well as developers, back in November we added the ability to create a scratch org in Gearset with just one click. Then more recently we released an update that allows you to choose the expiry period of your scratch orgs too, all with the ease of clicks-not-code.

    But there's always room for improvement. Creating scratch orgs and setting their expiry period is a great starting point, but there are lots more configuration options when creating a scratch org. To make this feature useful to DevOps teams, we need to support the full breadth of configuration options from Gearset's UI, without having to touch the command line.

    Gearset’s latest beta does just that, letting you create scratch orgs from any existing definition files and configure general settings, without having to resort to using the CLI. This means you can create highly tailored scratch orgs in a matter of clicks and integrate them seamlessly with Gearset’s existing comparison and deployment features.

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  • With great power comes great responsibility: team owners can now manage team members' automation jobs

    Ellis Toms on July 26th 2018

    Until recently only the person who created a CI, change monitor or test monitor job could edit, disable or delete it. This was fine most of the time but what if that person was on vacation for two weeks and their CI job needed to be paused or edited? Or you want to add your team’s email address to the notification settings of every change monitoring job? As a team owner you wouldn’t be able to do these things, instead you’d have to reach out to us to help you make these changes.

    But now, to help with these types of scenario we’ve added extra powers to team owners, giving them greater control and flexibility over managing their team’s automation jobs.

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  • Gearset’s static code analysis now runs on PMD 6.3.0

    Ellis Toms on July 12th 2018

    Gearset’s PMD-based static code analysis has been running on Enterprise users’ deployments and backups since the start of 2018, helping improve Apex code standards across Salesforce development teams.

    We’ve recently upgraded the version of PMD our static code analysis is built on, from 5.8.1 to 6.3.0. In this upgrade PMD fixed a few bugs but also added some useful and exciting functionality that you can take advantage of with Gearset. The new version brings the ability to suppress Apex code warnings, as well as 16 new rules, giving you more power to tailor your rule set to your needs.

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  • Adding regex patterns to object-level metadata filters

    Ellis Toms on June 28th 2018

    Every deployment in Gearset starts with a comparison between two environments, whether they’re Salesforce organisations or metadata stored in a git repo. Being able to compare the metadata between two environments has lots of advantages, one of the most important being the ability to quickly get an overview of all the ways in which they differ, and selectively deploy changes.

    That said, we’ve all had the dubious pleasure of working with environments that have diverged more significantly than we’d like, whether it’s due to teams working on features for the same org, a sandbox that hasn’t been refreshed in a long while or inheriting less-than-perfect legacy orgs. This can result in comparisons between orgs with thousands of differences, making it difficult to discern the changes you’re interested in deploying. It can also result in longer comparison times, as all of that metadata needs to be retrieved from Salesforce before it can be compared.

    We want to make configuring your comparisons and deployments as fast and easy as possible. So to help mitigate this problem, we’ve expanded on the ways you pick which metadata Gearset compares for you. Until today, the granularity of Gearset’s filtering was limited to either a whole metadata type, e.g. CustomObject, or specific named items within that type, e.g. Account. With the latest release, we’ve added the ability for users to add regex patterns to object-level filters and the option to specify items that they want to exclude from the comparison, speeding up deployment configuration and making it easier to ensure you’re only seeing the metadata you’re interested in.

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  • Automatically identify dependencies in Apex classes and triggers

    Ellis Toms on May 30th 2018

    Missing dependencies are one of the greatest pain points for Salesforce admins and developers - they block deployments, take hours to track down, and can involve a lot of manual XML editing. Gearset's problem analyzers scan your metadata and automatically identify and resolve these missing dependencies for you, making deployments a breeze.

    With our latest update, Gearset now understands and resolves dependencies within Apex classes and triggers. Referencing a new object in your Apex class? We'll spot it and make sure it gets included in your release. Does that new object have related profile and field level security changes? You can include those with just a click. The result is faster, smoother deployments and happier end users.

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  • Add outgoing webhooks to a CI job and Gearset will automatically post to any third party app

    Ellis Toms on May 16th 2018

    Gearset's built-in continuous integration (CI) is already a powerful tool, allowing you to automate large parts of your release management process. But what if you need to trigger third-party services as part of your release process, to run Selenium tests for example? Until now, this had been a manual process; when the CI job finished in Gearset, you had to remember to kick off those Selenium tests.

    With the latest release of Gearset, we've introduced the ability to add outgoing webhooks to your CI jobs. Any service with an API can now be triggered directly from within Gearset, letting you build a deployment pipeline tailored to the needs of your business.

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  • Gearset now uses API version 42 as default for Git repositories

    Ellis Toms on April 26th 2018

    As we've discussed in previous posts, choosing which metadata API version to use when storing your metadata in git requires some thought. If you've ever seen errors like: Property 'valueSet' not valid in version 37.0 or Not available for deploy for this API version, then you know what we're talking about.

    With Gearset, you can avoid the pain of deployment failures and fixing version mismatches through our intelligent handling of API versioning. When using source control as the source or target of a comparison, behind the scenes Gearset is taking the contents of that repository and running checks to determine the version of the metadata inside. Gearset has recently improved this handling, running even better checks to determine which API was used to generate the existing repository, and when an API version is not detected, Gearset will now default to version 42 rather than version 37. With this new default, anybody creating a new repository with Gearset will always have the latest and greatest metadata.

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  • New dependency support for deploying flows

    Ellis Toms on April 4th 2018

    Dependencies between objects are one of the most common causes of failed Salesforce deployments and finding missing dependencies can be seriously time-consuming and frustrating. But with Gearset’s dependency tracking, our users have been able to eliminate the trial and error from deployments so you can deploy quickly, confidently and successfully.

    Over the past two years we’ve been steadily adding support for more and more dependencies, based on our telemetry and user feedback. Our latest addition is dependency support for flows.

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  • You can now create validation-only CI jobs in Gearset

    Ellis Toms on March 20th 2018

    Gearset’s easy end-to-end continuous integration (CI) process already ensures our users all the benefits of reliable continuous delivery, without the need for external software like Jenkins.

    Now within Gearset, if you're an Enterprise-tier user you can set up validation-only CI jobs between any of your Salesforce orgs, so you can catch any problematic changes early and make sure that when the time comes to deploy, you’ll be able to release successfully.

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  • Data deployment update: Pick which dependencies to deploy and what field to use for upserting records

    Ellis Toms on March 15th 2018

    With a customisable test data set, automatic relationship handling and control over field mapping and upserting, Gearset makes it easy to execute complex data deployments. All you have to do is pick the records you want to deploy and Gearset will handle the rest.

    Gearset’s latest updates to our data deployment (beta) feature includes a new step between configuration and the deployment plan, where you can select which dependencies to deploy and customize field mapping for upserting records. With this easy deployment configuration and our “clicks-not-code” philosophy, Gearset allows you to migrate your data between your Salesforce environments in a matter of minutes, giving you more time to focus on your actual release.

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  • Feature update: Static code analysis now runs during your Continuous Integration jobs

    Ellis Toms on March 14th 2018

    Gearset’s customizable static code analysis helps teams develop high quality coding standards that fit their release process. As well as running during manual deployments and in change monitoring jobs, Gearset’s static code analysis now also automatically runs as part of your Continuous Integration (CI) jobs.

    Configure your rule set and Gearset will automatically perform your code analysis every time a CI job runs, making it easy to manage the quality and style of your Apex and ensure problems are caught early for all of your continuous deployments.

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  • Jira update: post deployment notes as comments to your Jira tickets

    Ellis Toms on February 5th 2018

    With Gearset’s Jira integration (Jira Self-hosted and Jira Cloud) you can effortlessly add Jira tickets to your deployment. Gearset automatically posts deployment updates to your tickets so you can see all the changes your team are making, keep up-to-date with the progress of tickets, and approve releases more efficiently.

    With the latest release, any deployment notes you attach will be included in both the deployment report and within the comments posted to your Jira tickets, allowing you to easily track every change that has been made and understand the context of why they have been made. Additionally, Gearset will now display any attached Jira tickets within your deployment reports for a clear and robust audit trail.

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  • Jira update: support for Jira Self-hosted (on-prem) instance

    Ellis Toms on January 18th 2018

    Gearset’s integration with Jira lets you automatically post deployment updates to your tickets and keep up-to-date with the progress of your user stories. Gearset now supports Jira Self-hosted (on-prem) as an instance type, as well as the default Jira Cloud instance.

    You can now also search and select which Jira ticket you’d like to add to your validation or deployment package from a dropdown list, rather than add your ticket reference manually.

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  • The entity: {object} does not have feeds enabled

    Oli Lane on December 13th 2017

    Salesforce’s support for Chatter feed tracking means that your users can be notified when certain objects they follow are updated. This makes it easy to see what’s changing in those objects directly inside your Chatter feed.

    Unfortunately, there are a couple of pitfalls when deploying Chatter feed tracking settings between Salesforce environments, and the most common is the error message:

    The entity: {object} does not have feeds enabled

    Gearset now has the ability to work around this deployment error for you, and detect it before you even try to deploy the changes.

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  • Improve the quality, performance and security of your code with Gearset’s static code analysis

    Ellis Toms on November 28th 2017

    To ensure that you are writing high quality, easily maintainable Apex code, it's important that you follow a few best practices in terms of code structure and content. With our latest release, Gearset now automatically performs static code analysis on the Apex in your orgs, helping you write higher quality and more effective code and ultimately speed up release cycles.

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  • An easier way to view failed deployments and validations with Gearset

    Ellis Toms on November 18th 2017

    Gearset has always endeavoured to increase the visibility users have into their Salesforce environments. As well as a complete history of successful deployments and validations, you can now view in-progress and failed deployments from the deployment history page as well as see which validations have failed under the validated packages page. Finding and fixing deployment issues is now faster and easier than ever.

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  • Working around the Custom Metadata Unknown_Exception issue in Salesforce

    Catherine Bacon on October 26th 2017

    One of our users ran into an unusual issue while running a seemingly innocent comparison. When comparing two Salesforce orgs to see the difference between them, Salesforce returned a cryptic error message: Unexpected_Exception: An unexpected error occurred.

    Generic error messages like this can me hard to deal with as they give you very little information to work with (as anyone who uses Ant will know). Gearset is all about surfacing and solving deployment issues, so we decided to investigate and find the underlying cause of the error. Thanks to some great feedback from the user in question, we managed to narrow down the cause of this error to very specific scenarios related to Custom Metadata and managed packages. We've updated Gearset so it'll suggest how to work around them more automatically.

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  • See the results of your Salesforce org tests on your desktop with Gearset’s CruiseControl integration

    Ellis Toms on October 3rd 2017

    Have you ever found that your tests have been silently failing, only discovering them when you tried to deploy? Gearset’s test automation makes it easy to track test status across all your orgs and get notified when things start to go wrong.

    As part of Gearset’s ongoing effort to increase the visibility teams have into their Salesforce environments, we have recently extended our test automation to integrate with CruiseControl. The result? See the status of your org tests right on your desktop.

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  • Deploying LeadConvertSettings with Gearset

    Ellis Toms on September 12th 2017

    Gearset makes deploying your Salesforce metadata ingeniously simple by giving you a visual comparison between your orgs before you deploy your changes. From Profiles, to Custom Objects, to LeadConvertSettings, Gearset can help speed up your deployments and automate those slow, manual tasks.

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  • Feature update: custom metadata filters are now shared with your team

    Jason Mann on July 14th 2017

    Custom metadata filters are a powerful way to optimise your workflow with Gearset. With a custom filter you can choose which metadata is retrived from Salesforce, speeding up comparisons between your orgs and making it easier to find the changes you're interested in deploying.

    Until now, these filters were unique to each user. With the latest release, custom filters are now shared amongst teams, making it easier for teams to collaborate and ensure they're all using the same filters for their deployments.

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  • Migrating quick fixes in Salesforce to source control

    Stephen Chambers on June 29th 2017

    Salesforce allows development teams to respond to changes in business requirements much more quickly than traditional platforms such as SQL Server or Oracle. When the need arises, the whole team, and especially admins, can make changes directly in the production org, bypassing the normal software development lifecycle.

    However, organisations adopt a software development lifecycle and Agile practices for a reason! Changes made directly in the org can often be overwritten at a later date by a scheduled deployment, or not get the proper scrutiny they deserve. Gearset's change monitoring has helped thousands of organisations track changes made directly in their orgs and bring them back into the development team's natural rhythm.

    With a recent release, we've extended this feature to make it possible to take changes that Gearset detected and move them directly to another org, such as downstream QA or development, or even push them through to your version control system.

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  • New alerting features in Gearset's Salesforce metadata monitoring

    Kevin Boyle on June 22nd 2017

    The flexibility of the Salesforce platform encourages change, allowing power users, admins and developers to easily tweak things as needed. As a company that builds a release management service, we encourage people to follow good development practices and ensure that changes are properly documented and audited so you can understand later why they were made! However, forcing every change through a software development lifecycle, even an Agile one, would be sacrificing the power of the platform and the clicks-not-code culture that allows organisations to make rapid change to their orgs as the business requires. After all, adding a simple picklist value doesn't carry the same risk as 10,000 new lines of Apex or addition of AppExchange packages.

    So how do you ensure that changes made directly in production by admins and power users aren't forgotten about and are properly captured and audited? That's where Gearset's change monitoring comes in. This was the first feature that we added to Gearset Enterprise, and it's now trusted by thousands of businesses to allow their Salesforce teams to properly capture every change, without compromising their ability to blaze a trail.

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  • Version control and metadata API versions

    Matt Dickens on June 22nd 2017

    Back at the start of the year, we wrote a post about Gearset intelligently handling API versioning so that you don't have to. We explained that Gearset will automatically pick the highest commonly-supported version between source and target and use that by default, while still allowing you to specify an overriding version, should you need to.

    As for version control repositories, Gearset treated these as containing version 37 metadata unless you applied the version override. This worked well enough, but came with the additional burden of having to pick an API version to use for each comparison when comparing to a source control repository containing anything other than version 37 metadata. In a recent change, we've made Gearset smarter when comparing to version control and uploaded metadata zips.

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  • How to temporarily disable continuous integration jobs in Gearset

    Stephen Chambers on June 8th 2017

    Gearset's continuous integration feature set has been evolving rapidly to better support mature application lifecycle management. This evolution has continued with our increased support for version control providers. Since we first added CI functionality to Gearset, with standard GitHub and Bitbucket version control included, we also now support GitLab, GitHub Enterprise, and more recently taken a huge leap forward to support any git-based source control repository to which Gearset has access.

    With our latest release, we've now added the ability to pause a currently active CI job. Disabling a CI job may seem a little counter intuitive, but does make sense for certain scenarios. Firstly, you may not want a CI job to start deploying changes at the same time as hotfixes or ad-hoc changes to the same target org are taking place. To help prevent potential conflicts, the CI job can now be paused, the ad-hoc changes can be safely deployed to production and the CI job can be reactivated when safe to do so. Alternatively, you may want to simply set up the CI job in advance, but not have it run until other parts of the overall process have been completed.

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  • More flexible team management in Gearset

    Stephen Chambers on May 25th 2017

    We're continually adding new features to Gearset with the goal of simplifying Salesforce release management for everyone, irrespective of job role and responsibilities. These can range from new standalone features, to the ongoing iteration and gradual enhancement of existing features driven primarily by user feedback.

    One of the most popular requests has been to improve the existing team management functionality in Gearset.

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  • Reduce noise when migrating Salesforce managed packages using Gearset

    Oli Lane on March 20th 2017

    Gearset is already great for migrating changes to managed packages, but one problem that customers sometimes run into is noise in the comparison viewer. If you've got lots of managed packages installed in your Salesforce orgs, it can be tricky to find the components you actually want to migrate, even with Gearset's advanced filtering capabilities. To make matters worse, your comparison times can be made significantly longer because Gearset has to download all that extra metadata from Salesforce.

    To address this problem, last week we introduced some extra filtering options that you can apply to your Gearset comparisons. You can now specify a list of managed package namespaces to include in your comparison, rather than simply including all or none of the packages. This means that Gearset no longer needs to download metadata from packages that you're not interested in, and your comparison is no longer cluttered up with it - leaving you free to focus in on the components you care about.

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  • Migrating customizations to Salesforce Managed Packages using Gearset

    Andrew Hunter on March 17th 2017

    When a managed package is installed into a Salesforce organization, that managed package can augment the organization with new metadata such as CustomObjects or by making modifications to existing metadata such as adding a new CustomField to a standard object. These modifications can be an issue when dealing with a traditional deployment tool like Ant, as all of this extra metadata will now be mixed in with your existing metadata.

    It’s possible to ignore this metadata altogether, but this can be an issue as it’s possible that you will customize some of it after installation, adding new fields that model your quoting process for example. Without careful tracking, it’s very hard to tell apart the metadata that the package installed from the customisations that you made to the package’s metadata.

    Gearset provides a solution to both these problems.

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  • How to deploy Salesforce Record Types

    Jason Mann on February 28th 2017

    We’ve recently noticed that more users are having issues deploying Record Types to Salesforce. This type of metadata has always been a bit tricky to deploy, and the introduction of Global Value Sets in Winter ‘17 has added a new variable to the mix.

    We’ve recently been improving Gearset’s dependency and problem analysis engine to help deal with some of the challenges of deploying record types and picklist fields.

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  • Back up your Salesforce metadata on-demand with change monitoring

    Oli Lane on January 26th 2017

    Gearset’s change monitoring feature gives you confidence that any changes made directly in your production instances will be easily detected and captured, so that you can propagate those changes back to development and staging environments and make sure they don’t get lost. Even better, if you discover some unexpected changes that you’d prefer got lost, Gearset offers simple, instant rollback to reverse those changes.

    The change monitoring feature also doubles as a backup tool. For any change monitoring job, you can view a list of every daily snapshot Gearset has taken, and download a copy the metadata as it was on that day.

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  • Property 'valueSet' not valid in version 37.0 - versioning and the mdapi

    Matt Dickens on January 3rd 2017

    If you've worked with the Salesforce metadata API for any period of time, you've probably seen a message along these lines:

    Property 'valueSet' not valid in version 37.0 - versioning and the mdapi

    This sort of error is likely fairly familiar to those teams opting to source control their metadata. The details my differ slightly, but the outcome is the same - a mismatched API version has caused a failed deployment by trying to push metadata that was retrieved using a newer version to an older version of the API. This raises the questions - what version should you use for the metadata in your repo, and at what point should you upgrade it? Read on to hear how Gearset makes this error message a thing of the past.

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  • Retrieving and deploying namespaced layouts in Salesforce

    Oli Lane on December 14th 2016

    TL;DR: Retrieving namespaced layouts from Salesforce doesn't act quite as you might expect. Gearset now works around this quirk, so that you don't have to think about it.

    Recently we received a slightly odd bug report from a user who claimed that Gearset was failing to include layouts inside namespaces in comparisons, despite the fact they had selected the Include managed packages option in the comparison filter. To add to the intrigue, the user was able to retrieve a list of the layouts using ANT, via a call to listMetadata() - this is exactly what Gearset does as its first step, so it was surprising that the layouts weren't showing up.

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  • Even better filtering of your Salesforce metadata

    Oli Lane on December 8th 2016

    One of Gearset’s best features is the ability to quickly see an overview of all the differences between two Salesforce orgs. However, if you're comparing particularly big orgs, or preparing a complex deployment, the list of changes can grow quite large.

    Earlier this year we expanded our support for these scenarios with advanced filtering queries. For most cases that was enough, but some users still found that they needed more control. This week we're releasing an overhauled filtering engine which provides granular, per-column filtering to make it even easier to drill down to the changes you care about.

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  • Deploying standard value sets in Salesforce

    Oli Lane on November 10th 2016

    The Salesforce Winter ‘17 release has brought with it a whole raft of great new features and no-brainer improvements to the platform. Inevitably, a few of those changes have required some adjustments, not least of which have been the changes to the structure of picklists.

    As a brief recap, many Salesforce standard objects have picklist fields - fields that allow only a restricted set of predefined values. Before Winter 17, these predefined values were stored with the field definition, but now they're stored separately. These new collections of values are called standard value sets. For example, the Type picklist on the Opportunity object now has its values stored in the OpportunityType standard value set.

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  • Turbocharge your Salesforce continuous integration jobs with GitHub webhooks

    Oli Lane on October 16th 2016

    Last week, we were thrilled to release one of our most anticipated features yet: built in continuous integration (CI) unlocks a whole new avenue of powerful release management possibilities. We’re not fans of resting on our laurels around here at Gearset HQ, though, so this week we’re already shipping a huge improvement to the way CI works with GitHub.

    By default, CI jobs run at 4-hourly intervals, automatically syncing changes from your source to your chosen target org. That’s great, but we can do better!

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  • Source control your Salesforce metadata with GitHub Enterprise and Gearset

    Matt Dickens on September 29th 2016

    tl;dr: Deploy metadata directly to and from GitHub Enterprise with Gearset. Read on to find out how to get started!

    When making the decision to version control your metadata, one of the first things you’ll need to figure out is where to host it. There are a variety of great options out there, but one of the first that’s likely to cross your mind is GitHub. Its ubiquity in the open source community and beyond not only means that it’s an incredibly well-documented platform supporting robustly exercised collaboration workflows, but it also means that most developers you meet will have certainly heard of GitHub and probably used it; the term “pull request” has entered into everyday developer parlance.

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  • Salesforce continuous integration with Gearset

    Jason Mann on September 20th 2016

    Continuous integration (CI) has been one of the most hotly requested features in Gearset. From keeping sandboxes in sync to pushing changes from source control to your dev org, continuous integration provides the power to streamline your releases.

    We’re excited to announce that Gearset now has CI built in. Create, monitor, and track continuous integration jobs between your Salesforce orgs, and even share the results with your team. It’s all the power and intelligence of Gearset, automated.

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  • Deploy metadata from a local file to a Salesforce org

    Jason Mann on September 2nd 2016

    Gearset gives you fine-grained control over what to include in your deployment packages, and our automatic dependency analysis helps spot missing components. But sometimes you just need run a deployment from metadata stored on your local machine, or make a few edits to a package before releasing.

    The new local file support in Gearset is here to help, giving you the flexibility to run a deployment no matter where your metadata is stored, while retaining the rollback, audit history and collaboration power of Gearset.

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  • An undo button for Salesforce metadata: Rolling back production changes

    Kevin Boyle on August 8th 2016

    Much of the power of Salesforce comes from quickly being able to respond to the fast changing needs of business user needs by making small changes directly in production. #AwesomeAdmins and Trailblazers everywhere can implement user requests without waiting to go through a long development and release cycle.

    With Gearset’s change monitoring you can be confident that any changes made directly in production will be easily picked up and captured in your regular development and staging environments ensuring that changes aren’t lost. After all, making changes directly in production is only great if they aren’t later overwritten by another well-meaning deployment!

    As more and more Salesforce developers and admins have started to use Gearset’s change monitoring, we’ve received some surprising feedback - even in well managed orgs there was a lot more happening in production than the development teams or release managers knew about.

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  • Unpicking Salesforce dependencies: Supporting formula dependencies in Gearset

    Matt Dickens on July 14th 2016

    We’ve spoken before about how dependencies between objects are the most common cause of failed deployments. There are a host of different dependency types, and failing to notice that one object is dependent on another when building a deployment package is likely to cause your deployment to fail.

    Thankfully, Gearset’s dependency tracking is here to help. Gearset checks for dependencies before pushing the deployment package up to Salesforce and warns you of any that are missing. Our goal is to eliminate the trial-and-error from deployment - when you click the “Deploy” button in Gearset, we want you to be confident that the deployment will succeed.

    Although we don’t currently detect all types of dependency, we’ve been steadily increasing our coverage over the past 12 months guided by our telemetry and, most importantly, feedback from you. Our most recent addition is detecting dependencies in formula fields.

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  • Better filtering of your Salesforce metadata

    Matt Dickens on June 30th 2016

    One of the big advantages of Gearset is that you can see all the metadata differences between two orgs, making it easy to build a deployment package containing just the changes you need. Unfortunately, when working on a large or complex deployment, these differences can be overwhelming. For example, you might want to deploy changes specific to a particular feature while leaving others out. This could mean there are be changes you're not interested in and even whole objects that you'd like to ignore.

    We've extended our filtering of comparison results by introducing two new prefixes, making it easier than ever to find the changes you're interested in.

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  • Sharing your Salesforce deployment history using the team features in Gearset

    Stephen Chambers on June 24th 2016

    Coordinating with team members to manage releases to your Salesforce environments can be one of the biggest challenges when attempting to create a robust deployment process. Clear communication to ensure everybody on the team knows who's doing what can be particularly tricky.

    Not being able to easily see what changes have been made to production, when, and by whom can have serious consequences, the most common being accidentally overwriting a colleague's changes.

    That's where the team features of Gearset can come to your rescue.

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  • Rolling back unwanted changes in a Salesforce deployment

    Jason Mann on June 22nd 2016

    Rolling back changes in Salesforce is normally a difficult, slow and frustrating process in which developers and admins must revert changes one at a time. But all that pain goes away when you start using Gearset.

    You can easily roll back changes from any deployment made through Gearset in a few clicks - whether that's reverting the entire package or only a few specific items. And you can manage the whole process through our intuitive user interface.

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  • The curious case of a stray ID

    Andrew Hunter on May 25th 2016

    One of our goals at Gearset is to turn Salesforce deployments into a single-click process, or as close as we can get to that! To this end, we check every deployment for potential problems before sending it to Salesforce and offer fixes for anything that could cause your deployment to fail. The most common is detecting missing dependencies but we also fix up issues with Master-Detail fields, history tracking, profile-mismatches and many other common problems. Our problem analyzer blog post provides more detail about the issues we can automatically check for.

    We’ve just added a fix for a problem that a user reported to us and it was so strange I decided to write it up so that it may help somebody in the future that comes across this problem.

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  • Deploying feature branches of your Salesforce metadata

    Stephen Chambers on April 18th 2016

    Our support for GitLab and GitHub has provided flexibility for people to use their existing source control solutions to compare and easily migrate Salesforce metadata changes.

    There has been one additional feature that's been missing from our initial support of the source control story, and that's been providing the ability to compare Salesforce metadata from a specific branch within a repository, often implemented when using a feature Branch flow.

    The good news - branch support is now available for GitHub and GitLab, and it's very easy to get started.

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  • Automatically detecting problems in your Salesforce Change Sets and deployment packages

    Stephen Chambers on April 4th 2016

    Have you ever experienced a failed deployment to one of your Salesforce orgs?

    Perhaps you've even experienced a deployment failure despite extensive preparation. All tests have passed and the validated deployment package is just waiting to go, and it's only after the process kicks off that it implodes and the deployment has to be rolled back while you pick apart the reasons.

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  • Source controlling Salesforce Metadata with GitLab

    Kevin Boyle on March 28th 2016

    Source controlling any software project has many advantages, particularly around audit and traceability, and Salesforce is no different. Using a version control system such as git for your Apex, VisualForce, or metadata helps developers and admins collaborate and understand what everyone is working on.

    Gearset has supported source control via GitHub since September 2015 and based on user feedback, we’ve now released support for GitLab.

    Gearset users requested GitLab support.
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  • Implementing Salesforce testing best practice with Gearset

    Jason Mann on March 17th 2016

    One of the challenges of managing a Salesforce organization is that undocumented changes can be made in Production which have knock-on effects on your existing unit tests (see our last blog post on why testing is important). These lurking test failures often lie hidden until deployment time, leading to unexpected deployment failures.

    In this post, we’ll look at how to use the test runner feature of Gearset to automate testing in your orgs and stop undocumented changes silently breaking your existing unit tests.

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  • How to deploy a Salesforce Sales Path

    Kevin Boyle on February 18th 2016

    In the words of Salesforce itself, Sales Paths are a feature of Salesforce that “keep sales reps focused on what’s most important to close deals fast. By guiding reps to the right fields and sales content at the right time, Sales Path enforces and ensures adoption of your company’s sales process.”

    These sound like a great addition to any Sales Cloud, but how do you deploy them?

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  • Roadmap review: Q4 delivered! Insight, deployment annotations and group notifications

    Jason Mann on December 16th 2015

    I’ll admit that when we first put our roadmap together back in early October, I was nervous. We committed to several major new features, the biggest of which being our org change monitoring service, Insight. This alone could easily have been enough to keep us busy until the end of the year. Feeling confident in our abilities, we scheduled a slew of user experience improvements and a major upgrade to the comparison engine that powers Gearset into the mix. Combined with the stress testing of a rapidly increasing user-base, it felt like an ambitious target.

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  • Learn what you want, when you want, with our new support videos

    Jason Mann on December 15th 2015

    Learning something new can be challenging. Whether you're picking up a sport or practising a new language, it’s always nice to have a helping hand to guide you. For many people, watching someone else perform a task first helps them learn faster and removes the fear of the unknown.

    We've been releasing some great new features for the app over the past few months, including org change monitoring and validated deployment packages. To ensure that everyone makes the most of these new features, we decided to create our new support videos, available on our revamped YouTube channel. They're also categorized on our support page to make it easy to find the right video for you.

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  • Give your Salesforce audit trail some context with deployment notes

    Oli Lane on December 14th 2015

    With its deployment history, Gearset Deploy already gives you a trail of what has been deployed into your Salesforce orgs and when. With the introduction of Insight, it can even do that for changes not made through Gearset. However, to get full use out of this trail of deployments you need to know the why, too.

    Today we're introducing a new deployment notes feature which gives you the ability to record that context: when you make a deployment, you can now attach notes to it to document why a change was made. That context could help tremendously 6 months down the line when you're trying to work out what happened!

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  • Understand your Salesforce changes at a glance with Gearset

    Oli Lane on December 8th 2015

    Let's be honest: XML object representations are an eyesore. They're verbose, they're hard to read, and they don't always map intuitively to the interface you see inside Salesforce.

    With Gearset Deploy, our goal is to build a deployment tool that really understands your Salesforce data. That's why this week we rolled out changes to our diff viewer which will make it possible to cut through the noise and see what you've actually changed, without trying to parse XML in your head.

    We're starting off with picklists, but we've also put work into our engine to make it easier to add other object types in the future.

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  • Introducing Insight for Gearset - automatic change monitoring for your Salesforce orgs

    Jason Mann on December 3rd 2015

    One of the last big roadmap releases for 2015 is our much-anticipated org monitoring service. It’s called Insight for Gearset, and we’re excited to announce it has now launched into our preview program.

    Here are just a few things you can do with Insight

    - Be notified when your Production org changes
    - Track all deployments, across all tools, with a complete audit trail
    - Download change reports for an org, providing a detailed change log
    - Catch undocumented or unscheduled changes directly in Production
    - Avoid overwriting others' changes by always being aware of updates
    - See who changed what, when, and why in your orgs

    Track all org changes with Insight from Gearset
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  • In field: summarizedField - no CustomField named {fieldName} found

    Luke Drury on November 25th 2015

    Roll-up summary fields

    Salesforce allows you to create roll-up summary fields on master objects, in a master-detail relationship. These roll-up fields perform calculations on the fields that they roll up, such as summing the numbers in that field. This is useful for things such as calculating the sum of certain kinds of invoices.

    Why deployments can fail due to roll-up summary fields

    Roll-up summary fields have dependencies on a couple of other fields. They depend on the field they're rolling up in the target object, and also the master-detail relationship field in the target object - Salesforce calls these the Read the rest of this post



  • Validate your deployments ahead of time with Gearset

    Jason Mann on November 12th 2015

    When you’ve got a crucial deployment to make or a narrow release window, the last thing you want to spend valuable time on is picking apart why a deployment failed or rebuilding the package on the fly. One way around this is to check ahead of time that your deployment package will successfully deploy. The deployment can then be swiftly promoted on demand, safe in the knowledge that the tests have passed and you haven’t missed any crucial dependencies. We call these validated packages, and they're a great way to reduce deployment failures and make release day that little bit less stressful.

    Today we launched the first stage of support for validated packages: Gearset now allows you to create and validate your deployment package without actually running a deployment. You can then come back later to kick off the deployment, knowing that everything has already been tested.

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  • The entity: {object} does not have history tracking enabled

    Luke Drury on November 9th 2015

    Tracking changes to CustomObjects

    In Salesforce it's possible to enable history tracking on custom and standard objects. Once you've done this, you can then turn on history tracking on a per field basis, and so track changes to fields you're interested in.

    Why deployments can fail due to changes in history tracking

    In Gearset we break objects down into sub-components during the comparison, giving you control over which changes to an object you want to deploy. An example of this is standard objects and their fields. For example, you can deploy a new picklist value on a field without also deploying changes to the parent object to which it belongs, or changes to other fields in that object.

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  • Sick of checkboxes? Saved comparison options are here!

    Oli Lane on October 16th 2015

    As the first of a series of usability enhancements that we outlined on our roadmap this week, we're rolling out a small but significant change which we hope will really improve your day-to-day interaction with Gearset Deploy.

    You can now save your own custom comparison sets and retrieve them next time you want to compare the same metadata types. No more manually selecting checkboxes every time: just select your custom set from the drop-down menu.

    Here's how it works.

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  • GitHub integration has arrived!

    Spencer Thang on September 10th 2015

    Supporting continuous integration (CI) has always been part of our vision for Gearset Deploy. Continuous integration allows you to merge developer working copies to a shared main repository at scheduled intervals, reducing integration bugs and keeping the main repository current.

    In preparation for continuous integration, we've added support for comparing GitHub repositories with Salesforce organizations. With this new feature, you can easily view changes between developer working copies and deploy metadata directly to your Salesforce organizations.

    In the near future, you'll be able to schedule these comparisons and deployments at regular intervals, making integration a pain-free process. Here's how to get started.

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  • Destructive changes are easy with Gearset Deploy

    Jason Mann on September 3rd 2015

    In the productive world of Salesforce, deleting objects and fields can be a pain. Unsupported by change sets and difficult to master with the Force.com migration tool, the simple deletion of a few objects can bring seasoned admins to their knees. That doesn’t sound like the kind of Salesforce experience everyone hopes for.

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  • Walkthrough: using Gearset to deploy changes from a production to a sandbox Salesforce organisation

    Jason Mann on July 13th 2015

    Prompted by a question on the Salesforce Stack Exchange, I wanted to demonstrate how easy it is to use Gearset Deploy to manage migrating a Salesforce app from your production org to a sandbox.

    Gearset Deploy is designed to allow you to quickly synchronize your Salesforce orgs, search for and select the changes you want to make. It’s all done through the UI, and it includes highlighted line-by-line differences and dependency analysis to increase your deployment success rate.

    This post is a short walkthrough of how you would go about moving some changes or an app from production to sandbox.

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  • Designing Gearset Deploy: accessing your Salesforce deployment history

    Jason Mann on July 10th 2015

    To ensure the ongoing design and feature development of Gearset Deploy continues to meet our customers’ needs, we’re always listening to your feedback. One topic that has cropped up consistently is to provide a way to access a history of previous Salesforce deployments within the business. We’ve heard of situations where changes are being manually saved in a document, or even written down, in an attempt to keep track of what’s been updated. In this post we'll look at why it's important to keep a deployment history and how you can manage your deployment history in Gearset Deploy.

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  • Weekly Update: No more downloads, Gearset Cloud is here!

    Kevin Boyle on July 8th 2015

    Feedback from our users has been really positive, and Gearset Deploy is helping people move changes between their Salesforce orgs with ease, but our number one request has been to provide a cloud version so that people don't need to install anything or keep it up-to-date.

    In this week's update, I walk through the cloud version of Gearset Deploy and show how easy it is to get started.

    If you want to try out the new cloud version, just visit gearset.com to get started.

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  • Weekly Update: Minimizing Salesforce deployment failures using Gearset’s new dependency analysis

    Kevin Boyle on June 26th 2015

    Salesforce developers and admins often suffer come deployment time trying to work out the correct order in which to deploy things so that the deployment succeeds. Lots of time is spent tearing apart Profiles and PermissionSets to find the smallest slice that can be deployed to meet that end-of-sprint deadline. We end up doing tedious work, instead of the valuable work we should be doing for our businesses.

    This video shows the latest addition to Gearset in our quest to make all your deployments simpler. We're adding dependency analysis to metadata objects so you can automatically deploy the slices of Profiles and related objects when you make a change in your Salesforce org.

    If you want to try out this dependency feature on your deployments then get in touch at [email protected].

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  • Secure authorization for your Salesforce orgs: implementing OAuth in Gearset Deploy

    Matt Dickens on June 11th 2015

    We’ve recently been hearing from our more security-conscious users that they’d like to use OAuth to grant permissions to their organizations – in fact, it’s right near the top of our most requested features in UserVoice.

    OAuth has been one of our most requested features

    We know that for our users, their Salesforce organizations are at the heart of their businesses and the safety of these organizations is of the utmost importance. With that in mind, the latest release of Gearset Deploy offers OAuth as the default mechanism of connecting to organizations.

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  • Designing Gearset Deploy: enhanced filtering of Salesforce metadata

    Stephen Chambers on June 4th 2015

    We’re constantly evolving Gearset Deploy and spending a great deal of time making sure that performing your Salesforce deployments is a simple process. We’d like to share our current ideas for future features and get your thoughts on the designs that are on our roadmap. This blog post details the feedback we’ve had about the current Gearset Deploy filtering feature, and how it could be even better in future versions.

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  • Large Salesforce orgs and the 10,000-item API limit

    Chris Hurley on May 19th 2015

    Gearset Deploy is designed to retrieve metadata from Salesforce organizations in order to compare them and identify the operations required to deploy changes between them. This information is obtained through the Salesforce Metadata API, which can be queried for specific object types or names and provides a .zip file containing the requested metadata.

    However, when registering large organizations, it’s easy to run into its limits. Calls retrieving metadata can only request up to 10,000 files or 400MB at a time, and attempting to retrieve more than this results in failure. Tools designed primarily for Apex development, such as the Force.com IDE and MavensMate, are less likely to hit these limits because they’re geared towards working only with a subset of the objects in your organization. When comparing and deploying entire organizations, though, it becomes increasingly likely that the limits will be exceeded. If you’ve used the Force.com Migration Tool, which is a wrapper around the Metadata API, you may have come across these limitations yourself.

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  • Who made that change to my Salesforce metadata, and when?

    Kevin Boyle on April 9th 2015

    Salesforce organizations can quickly become complex: after all, they drive your entire business process and help your users succeed, so a certain degree of complexity is inevitable. This means it's especially important that deploying changes between organizations is as simple as possible.

    Gearset Deploy makes it easy to see what has changed, but some of our users told us they'd also like to see who made each change and when, so that they'd have all the context to understand what should be deployed.

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