Just to recap, so far our ongoing series about the Istio service mesh we’ve talked about the benefits of using a service mesh, using Istio for application deployments and traffic management, and how Istio helps you achieve your security goals. In today’s installment, we’re going to dig further into monitoring, tracing, and service-level objectives.

Elastic Stack Features (formerly X-Pack) is an Elastic Stack extension that bundles security, alerting, monitoring, reporting, and graph capabilities. One could use either all or specific components.

A couple of months ago we released the all-new Anodot.com. Following the release, I explored our Google Analytics account to see what had happened post-launch. I have always been ambivalent about Google Analytics. On the one hand, the service has helped shape web analytics as we know it today and is used by nearly every website. Not to mention it’s free and rather easy to consume. On the other hand, GA is never a slam dunk.

Did you ever have your customer success team (if you have the chance to have one!) overwhelmed by customers throught the support chat when facing minor incidents or even major outages, having to update all those worried customers in real time throught dozens of different channels as the engineering team finds out and resolves the issue? Support costs time, energy and money. What if all of your users could all connect to one single status page that would answer all of their questions?

As the threat landscape continues to expand, having end-to-end visibility across your modern application stack and cloud infrastructures is crucial. Customers cannot afford to have blind spots in their environment and that includes data being ingested from third-party tools.

Go behind the scenes with the Jira team and see how we performance-engineered our way to a zero-affinity cloud architecture that runs at enterprise scale. Performance engineering is a big deal when you’re serving millions of users from every corner of the globe. We previously wrote about a large engineering transformation program for Jira & Confluence, which we codenamed Vertigo – read more about the overall program here.

In an attempt to jump on the Kubernetes bandwagon, more and more managed Kubernetes services are being introduced. In a previous post, we explored how to deploy a Kubernetes cluster on Amazon EKS. This time, we will cover the steps for performing a similar process, this time on Google’s Kubernetes Engine.

Sentry’s newest features provide both macro- and micro-level perspective of trends in your errors and application’s health. They’re great — you’ll see.

Datadog is pleased to announce the availability of Synthetics, a whole new layer of visibility on the Datadog platform. By monitoring your applications and API endpoints via simulated user requests, Synthetics helps you ensure uptime, identify regional issues, track application performance, and manage your SLAs and SLOs. By unifying Synthetics with your metrics, traces, and logs, Datadog allows you to observe how all your systems are performing as experienced by your users.

Since its release in 1995, PHP has been one of the most popular server-side languages for building web applications. It supports a wide range of web servers, databases, and operating systems. PHP developers use popular frameworks like Laravel, Symfony, and Zend to deploy and manage sites that serve high volumes of traffic. To help you monitor PHP performance, identify bottlenecks, and optimize your users’ experience, we’re pleased to announce APM & distributed tracing for PHP.