Operations | Monitoring | ITSM | DevOps | Cloud

Synthetics

Run Datadog Synthetic tests in Azure Pipelines

Continuous integration (CI) demands continous testing: shifting left helps prevent faulty code from spreading, which is one of the core aims of CI. Datadog’s new Azure DevOps extension enables you to seamlessly incorporate integration and end-to-end tests into existing CI/CD workflows on Azure Pipelines, a dedicated CI/CD service that automatically runs builds, performs tests, and deploys your services and applications via cloud-hosted pipelines.

Why You Need Synthetic Monitoring

Synthetic monitoring can be one of the most powerful tools in your DevOps team’s toolkit, especially for the SRE, yet is one that is often overlooked by people building out a reliability mindset. Synthetic monitoring permits you to simulate any transaction or interaction users can have in your website or app, from places around the world, as often as you’d like.

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The Importance of Observability for Site Reliability Engineers (SREs)

Site reliability engineers (SREs) play a crucial role in ensuring the reliability of systems. From creating software to improving system reliability in production, responding to incidents, and fixing issues, SREs are responsible for guaranteeing the health of applications.. And observability helps support SREs'. Because an observable system allows them to identify and fix issues promptly, resulting in SRE's being better equipped to fast-track development cycles.

Synthetic Monitoring of Microsoft AVD Service Levels

We recently announced a FREE ready-to-go standalone SaaS logon simulator tool for Microsoft AVD, available here. This joins our fully featured logon simulator available for use on-premises, as SaaS or in the cloud within our synthetic monitoring suite. A logon simulator, whilst a useful tool, should be used in conjunction with other synthetic and real user monitoring tools for a truly proactive IT strategy designed to prevent real users encountering issues and raising support tickets.

Synthetics 8.4.0 - Elastic Observability

Elastic 8.4.0 was released in August. In this video we cover what's new in 8.4.0 Observability, and go through demos of the newest features in monitor management, data retention, and the public beta. Join Synthetics Tech Lead Andrew Cholakian, and Synthetics Engineer Justin Kambic for the latest in Elastic Synthetics.

Synthetic Monitoring for Windows, VDI & 2FA | 2 Steps

We relate synthetic monitoring to a heart rate monitor for application performance. It fits hand in glove with real user monitoring and provides insights into how real customers and employees are experiencing the application. Historically, we’ve seen limitations with real user monitoring. If nobody is on the network or using the application, then you're not receiving any performance data. Also, the performance data that you typically receive is from a panel rather than every single user.

Splunk Synthetic Monitoring in Splunk Observability Cloud - Product Demo

Splunk Synthetic Monitoring is now available in Splunk Observability Cloud allowing IT and engineering teams to proactively detect issues impacting web and API performance and end-user experience and troubleshoot and remediate issues in the web browser, the server, or a third-party dependency—all within a single UI. Watch this quick demo to learn more.

Monitor your gRPC APIs with Datadog Synthetic Monitoring

gRPC is an open-source Remote Procedure Call (RPC) framework developed by Google and released in 2016. Although gRPC is still relatively new, large organizations are adopting it in increasing numbers to build APIs that connect complex microservice meshes that use disparate languages and frameworks. gRPC-based APIs can perform requests up to seven times faster than REST APIs and enable customers to easily implement SSL authentication, load balancing, and tracing via plug-in libraries.

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Modern Observability and Digital Transformation

For most businesses, effective digital transformation is a key strategic objective, and as computing infrastructure grows in complexity, end-to-end observability has never been more important to this cause. However, the amount of data and dynamic technologies required to keep up with demand only continues to increase, and current tools are not equipped to handle it- with any discrepancies resulting in rising costs and reduced competitiveness.