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Tag: LocalStack

LocalStack Extends Emulation Reach to Microsoft Azure Services

LocalStack has made available a public beta of its platform that enables application developers to emulate Microsoft Azure cloud services on their local machines.

Colin Neagle, head of marketing for LocalStack, said LocalStack now enables application developers to build software locally that can run across more than 40 Azure services. Following initial support for cloud services from Amazon Web Services (AWS), demand for support for the Azure cloud services provided by Microsoft ranks highest among application developers, he added.

The challenge LocalStack needed to overcome is that Microsoft Azure cloud has a lot of unique database and serverless computing services and an infrastructure-as-code (IaC) tool, dubbed Bicep, that needs to be supported alongside other IaC tools such as Terraform, noted Neagle. The goal is to make support for all those Microsoft services generally available in early 2027, he added.

Designed to be deployed using containers, LocalStack claims there are now 1,500 organizations that have given application developers access to LocalStack. In total, more than 18 million active sessions are being spun up weekly, according to the company.

Additionally, the number of sessions should exponentially increase as application developers start to rely more on AI agents running in a local sandbox environment to build software, noted Neagle. That isolated sandbox environment also lowers risks compared to deploying an AI agent in a cloud computing environment, he added.

Application development teams can also reduce cloud computing costs by relying more on local machines to build software in a way that makes it simpler for them to debug code without having to access a cloud service, said Neagle.

Each DevOps team will need to determine how much to require developers to build and deploy software in the cloud. The majority generally prefer to use local machines to reduce latency, but that often creates issues when the code developed locally fails to run in a production environment. LocalStack is making a case for an emulation capability to eliminate the friction. The company is also moving to extend the scope of the cloud services it supports to include code destined to run on software-as-a-service (SaaS) applications following its acquisition of WonderTwin AI last month.

Regardless of the type of cloud platform used to build and run applications, there is a clear need to bridge a divide between how most developers prefer to work and the production environments where software ultimately is deployed.

Hopefully, there will come a day soon when the level of friction that DevOps teams historically encountered when building and deploying software will be sharply reduced. In the meantime, however, software engineering teams, after initially using AI to mainly generate code faster, are now extending the reach of those tools and platforms deeper into their DevOps workflows. The challenge and the opportunity lie in finding a way to safely and reliably achieve that goal when the output generated by AI tools can vary widely from one minute to the next.

October 12, 2026
LocalStack Acquires WonderTwin AI to Gain SaaS App Emulation Platform

LocalStack this week revealed it has acquired WonderTwin AI, a provider of an emulator of software-as-a-service (SaaS) applications that is used to build custom applications for those platforms.

Colin Neagle, vice president of marketing for LocalStack, said the emulators WonderTwin AI has developed will be integrated into the company’s namesake emulation platform that application development teams currently rely on to emulate cloud services provided by Amazon Web Services (AWS).

LocalStack and WonderTwin AI make it possible for application developers working on a local machine to build applications that are designed to be deployed on some type of external cloud platform using a local sandbox to test and validate integrations without having to connect to a service or build against a live application programming interface (API). That issue has been especially critical in an era where more code will soon be generated by AI coding agents that may for one reason or another circumvent the guardrails that might have been put in place to limit access to sensitive data.

The overall goal is to make it possible for application developers to experiment and iterate without waiting for access to shared environments that might not provide the level of interactive feedback required or increase costs as, for example, live APIs are invoked.

In general, application developers still prefer to build software on a local machine that they have more control over. LocalStack was created to provide a local instance of an AWS environment that enables developers to build software that is destined to run in a cloud environment. The goal is to reduce the number of instances where code that runs on a local machine doesn’t actually run as intended in the cloud.

It’s not clear how much code is developed first on a notebook, desktop PC or local server, but in the age of artificial intelligence (AI) the amount of code being generated by individual developers is increasing exponentially. Every time code has to be sent back for revision, it slows the overall pace of application development.

The speed at which DevOps teams make that adjustment will naturally vary from one team to another, but the sooner everyone realizes that a piece of AI-generated code might not run as intended in a cloud computing environment, the less stress there is likely to be for all concerned. The challenge and the opportunity, of course, is identifying those points of friction before the amount of code being created by AI agents might soon become too overwhelming to effectively deploy and manage.

Ultimately, DevOps teams need to meet application developers where they proverbially are rather than forcing them all to develop applications in the cloud. The simple truth is many developers, if inclined, will simply evade any cloud mandate using shadow IT resources they are well able to deploy and manage. The challenge, as always, is finding a way to centrally manage development environments in a way they will actually embrace versus passively resist.

September 15, 2026
LocalStack Adds Ability to Visually Debug AWS Apps on Local Machines

LocalStack today announced it has extended its ability to simulate Amazon Web Services (AWS) environments to provide an ability to debug applications before deploying them.

Colin Neagle, head of marketing for LocalStack, said App Inspector makes it possible for developers to debug their applications running in a simulated AWS environment inside a container on a local server.

Simulating the full application stack within a local sandbox container makes it possible to better understand application behavior such as data flows between AWS services, event execution paths and resource dependencies that may have been inadvertently misconfigured, noted Neagle.

Once discovered, App Inspector then generates a visual representation of the interaction between services in the local environment to make it simpler to debug applications without digging through logs and then needing to upload a fix to a staging server running in the AWS cloud.

That capability doesn’t replace the need for an observability platform but it does reduce the overall amount of friction software engineering teams are likely to encounter as they build applications on a laptop or local server, said Neagle.

In general, application developers still prefer to build software on a local machine that they have more control over. LocalStack was created to provide a local instance of an AWS environment that enables developers to build software that is destined to run in a cloud environment. The goal is to reduce the number of instances where code that runs on a local machine doesn’t actually run as intended in the cloud.

At present, LocalStack supports AWS, but the company is also building a set of emulation services for Microsoft Azure that will be made available later this year.

It’s not clear how much code is developed first on a notebook, desktop PC or local server, but in the age of artificial intelligence (AI) the amount of code being generated by individual developers is increasing exponentially. Every time code has to be sent back for revision, it slows the overall pace of application development. DevOps and platform engineering teams will need to streamline workflows in a way that ultimately improves productivity.

The speed at which DevOps teams make that adjustment will naturally vary from one team to another, but the sooner everyone realizes that a piece of AI-generated code might not run as intended in a cloud computing environment the less stress there is likely to be for all concerned. The challenge and the opportunity, of course, is identifying those points of friction before the amount of code being created might soon become too overwhelming to effectively deploy and manage.

Ultimately, DevOps teams need to meet application developers where they proverbially are rather than forcing them all to develop applications in the cloud. The simple truth is many developers, if inclined, will simply evade any cloud mandate using shadow IT resources. The better part of valor then is to enable application developers to build applications on the platforms they prefer in ways that can still be centrally managed by a DevOps team.

April 29, 2026
LocalStack Revamps CLI for Emulating AWS Cloud Services on Local Machines

LocalStack at the KubeCon + CloudNativeCon Europe conference this week unveiled a revamped command line interface (CLI), dubbed 1stk, for its framework that enables emulations of Amazon Web Services (AWS) environments to be run on a local machine.

The CLI in version 3 of the AWS 2026 edition of the framework, in addition to providing a single binary that is easier to install, also adds a Terminal UI (TUI) that walks developers through steps such as authentication or setting up an AWS profile. Additionally, it offers better log viewing, which is now also turned off by default.

At the same time, LocalStack has extended its Resource Groups Tagging API (RGTA) to enable developers to query and manage tags across multiple AWS services. Elastic Kubernetes Services (EKS) and CloudWatch resources are now fully integrated with the RGTA, and support for the Elastic Compute Cloud has been extended to provide an API for creating and deleting actual fleets of IT infrastructure resources versus providing a set of mock responses. Support for the libvirt VM manager is planned for a future release.

Finally, LocalStack as previously promised has now consolidated its community and enterprise edition into a single platform and removed continuous integration (CI) credit limitations from all tiers, including the non-commercial free tier. As of now, an auth token or continuous integration (CI) auth token is also required to start LocalStack for AWS.

LocalStack CTO Waldemar Hummer said that, in general, application developers still prefer to build software on a local machine that they have more control over. LocalStack was created to provide a local instance of an AWS environment that enables developers to build software that is destined to run in a cloud environment. That approach reduces the number of instances where code that runs on a local machine doesn’t actually run as intended in the cloud, noted Hummer.

At present, LocalStack supports AWS but the company is also building a set of emulation services for Microsoft Azure that will be made available later this year.

It’s not clear how much code is developed first on a notebook or desktop PC, but in the age of artificial intelligence (AI) the amount of code being generated by individual developers is increasing exponentially. Every time code has to be sent back to be revised only serves to slow the overall pace of application development. DevOps and platform engineering teams will need to streamline workflows in a way that reduces the amount of overall friction that is currently encountered as code moves into a production environment, noted Hummer.

The speed at which DevOps teams make that adjustment will naturally vary from one team to another, but the sooner everyone realizes that a piece of AI generated code might not run as intended in a cloud computing environment the less stress there is likely to be for all concerned. The challenge and the opportunity, of course, is identifying those points of friction before the amount of code being created might soon become too overwhelming to effectively deploy and manage.

March 24, 2026