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Mar 15, 2023   |  By Oguzhan Ozdemir
Cloud-native applications are designed as small, distributed microservices. The microservice applications are deployed as containers to ensure scalability, reliability, and portability. Kubernetes has become the de facto container management platform for the easy creation and management of large clusters. The most important aspect of microservices is their reliance on other microservices within the cluster.
Mar 8, 2023   |  By Ismail Egilmez
As more and more companies migrate their complex applications to the cloud, the need to deploy cloud infrastructure at scale is also increasing. Enterprises can no longer scale their deployments if they are provisioning infrastructure manually via cloud dashboard or CLI tools. This is where tools like HashiCorp’s Terraform come into the picture.
Feb 22, 2023   |  By Ismail Egilmez
A cloud application is a software application that runs on a cloud computing infrastructure, rather than on a local computer or on-premises server. Cloud applications are designed to be accessed over the Internet and typically rely on a web browser or mobile app to provide users with access to the software. Cloud infrastructure provides the necessary resources and services for the application to run, such as servers, storage, and databases.
Dec 14, 2022   |  By Tolga Takir
In a modern software development process, several steps are typically carried out to create a software system. These steps often build on each other, with each step providing the foundation for the next. One important step in this process is integrating code from different developers into a single codebase. This typically involves merging the code changes made by different developers into a common repository, such as a version control system.
Dec 14, 2022   |  By Sarjeel Yusuf
The shift to cloud computing and distributed systems has brought about many benefits, but it has also introduced new challenges when it comes to debugging. Traditional debugging methods such as logging and breakpoints can be less effective in these environments because they often rely on a central point of control and visibility. In a distributed system, there may be multiple components running in different locations, making it difficult to track down the root cause of an error.
Dec 7, 2022   |  By Ismail Egilmez
Continuous integration (CI) is a DevOps practice whereby code contributed by engineers is integrated into a project frequently and automatically. CI involves the use of a shared version control system (VCS), which is usually accompanied by other tools (including testing tools,) to manage source code. Engineers push code changes using the shared VCS; the code is then reviewed and tested before the build process is completed. This entire process is automated to maximize speed and performance.
Nov 29, 2022   |  By Oguzhan Ozdemir
One of the biggest challenges for running latency-sensitive applications on Lambda is cold-start issues. It’s especially difficult to choose when the runtime is something heavy, like Java. People are working constantly to improve the performance of serverless Java applications.
Nov 25, 2022   |  By Serkan Özal
APIs play a critical role in the overall performance of an application because it benefits customers to streamline the purchasing of their products and services. APIs should be correct, fast, secure, available, and reliable. Developers can determine API performance by defining performance tests—functional and load tests—and monitor it by tracking various metrics like the number of requests to API endpoints, time taken by an API endpoint to respond, and the amount of data responded to.
Nov 10, 2022   |  By Oguzhan Ozdemir
AWS constantly improves the overall performance and tooling around AWS Lambda. The recent addition to this trend is the Lambda Telemetry API which enables its users to have increased observability around their Lambda functions.
Aug 29, 2022   |  By Suleyman Barman
In modern technology, new applications are developed rapidly, and organizations are using cloud computing heavily for application deployment. In this context, Application Performance Monitoring (APM) plays a significant role in the monitoring and performance of software applications. APM helps organizations provide services to in-depth observability of the application. In addition, APM helps identify problems related to the application and performance issues.
Nov 11, 2022   |  By Thundra
Serverless reduces time to production drastically. However, understanding the root cause of incidents in distributed event-driven architectures is tough without having a sophisticated toolset. In this webinar, witness the great serverless journey of Leadent Digital, one of the UK’s leading technology and consultancy firms. You will hear from Ross(Leadent Digital, CTO) and Paul(Head of Software, CTO) about why they had a need for monitoring their serverless architecture and which pain points Thundra APM addressed to help them optimize the health and performance of their serverless systems.
Jun 1, 2022   |  By Thundra
Gain highlights on key CI metrics such as workflow & test success/failure rate, cost, and duration as well as test run history, logs, etc.
May 16, 2022   |  By Thundra
ServerlessDebugger is a live #AWS #Lambda debugger, provided by Thundra. It enables developers to #debug Lambda functions with ease, with no need to simulate, reproduce or redeploy.
Apr 27, 2022   |  By Thundra
Using Thundra APM, you can remotely debug your application before you push it to production.
Apr 26, 2022   |  By Thundra
Using Thundra APM, you can Remotely debug your application before you push it to production.
Apr 21, 2022   |  By Thundra
We improved the way you connect your workflows. With this update, we are also introducing Foresight’s Test Report Uploader step for your GitHub Actions workflow. You can pick your test framework, and our test report uploader automatically analyses each of your test runs.
Aug 4, 2021   |  By Thundra
Gain full observability for your CI Pipeline with Foresight. Identify slow and flaky tests, get to green builds faster.
Jul 2, 2021   |  By Thundra
Unlock Visibility into the CI Pipeline & Spot Test Failures in no time! Efficient microservices testing requires observable CI pipelines. By providing observability into the CI process, Thundra Foresight helps optimize the build duration and minimizes failed builds, enabling more frequent deployments, higher development productivity, and lower CI costs.
Apr 15, 2021   |  By Thundra
Remote debugging in distributed environments is painful. Thundra Sidekick is more than just a remote debugger. It's secure and easy to use. When developers push their code to remote development or staging environments in pre-production, they usually lose the ability of traditional debugging with breakpoints. Instead, they have to read the logs carefully and understand what’s going wrong.
Apr 13, 2021   |  By Thundra
Debugging, as in the form with breakpoints, is dead with the advent of distributed microservices. It's usually a problem to debug a remote microservice using intrusive methods because you can interrupt a user and/or another service that's using the debuggee service. Thundra Sidekick resurrects the debugging in microservices with non-intrusive breakpoints that could gather the same information a normal breakpoint would capture.
Dec 4, 2020   |  By Thundra
Debugging in production can provide an opportunity to pinpoint bugs that might not be apparent in the development or staging stacks. In this whitepaper, we will discuss how to effectively debug in production.
Oct 30, 2020   |  By Thundra
Kubernetes is a complex system but not a complicated one. Its layered architecture is open to creating disasters caused by networking, security, configuration, and cloud provider limitations. Learning from others' mistakes is the new reality of succeeding for cloud applications. This perfectly applies to Kubernetes-based software architectures and your software, too. If you don't understand how other people will fail, it's more likely that you'll fail at some point.
Sep 10, 2020   |  By Thundra
Learn how you can gain observability through serverless architectures with native tools like AWS X-Ray, open-source solutions like OpenTelemetry, and automated solutions like Thundra! This paper walks through the problem of serverless observability. It starts by defining the observability problem space, explaining how debugging and tracing are only part of a larger picture of application behavior. We'll explore AWS CloudWatch and X-Ray as a first attempt at observability. Then we will detail several open source serverless availability tools, before discussing Thundra's automated approach to observability.
Jun 10, 2020   |  By Thundra
Moving to a modernized cloud-native environment can remove many challenges. Instead of worrying about underlying infrastructure, you can focus on building new features and innovating. But companies can face new complexities such as understanding an application's health. Download this eBook to better understand these complexities and to manage large-scale microservices applications across development, testing, staging, and production environments using Thundra on Amazon Web Services (AWS).
Apr 25, 2019   |  By Thundra
Discover different ways of achieving observability in stateless, distributed, and event-driven architectures.
Jan 9, 2019   |  By Thundra
Built for straightforward debugging, monitoring, and observability, Thundra provides deep insight into your entire serverless environment.

Quickly pinpoint problems in Serverless. Thundra provides full observability, debugging, and performance monitoring for serverless development and operations teams.

Thundra is a software organization dedicated to helping serverless applications become a mainstream production reality for all enterprise organizations by shedding light into black box environments. With rich visualizations of aggregated metrics, logs, and traces, software teams can quickly identify and solve performance problems in their AWS Lambda environments with minimal to zero coding and no additional overhead.

Thundra provides answers quickly:

  • Maximize Developer Productivity: Focus on developing valuable business features and spend less time manually implementing monitoring tooling and debugging application problems.
  • Lower Costs and Resource Consumption: Identify what areas of your application are taking up the most resources in order to maximize efficiencies and reduce overall consumption.
  • Analyze from a Single View: Understand how your serverless applications interact with external services and, with integrations, analyze your serverless system alongside all your other data.

Pinpoint your serverless problems and get back to coding.