So far in our series on scaling observability for game launches, we’ve discussed ways to 1) quickly analyze large volumes of telemetry data and, 2) ensure high-quality telemetry data for more effective analysis at lower costs. The best practices in these blogs outline best practices for scaling observability during game launch day – which is necessary to ensure high performance across all infrastructure components – to ensure no lag, no glitches, and no bugs.

HashiCorp Consul began as an open-source project for service discovery. It has evolved to provide other valuable functionality like secure service mesh to help secure microservice architectures based on service identity, but also the ability to achieve repeatable application deployment lifecycles via Network Infrastructure Automation and control access to the service mesh via Consul API Gateway.These features are considered the four core pillars of Consul service networking.

If you’re wondering if that classic car you’ve been scoping out on Bring a Trailer or eBay Motors is as authentic as posited by the seller – specifically re: the common claims of “original paint” or “high quality respray” – you’re going to want to take a closer look around the edges. This is because a talented painter can make a second or 30th-hand vehicle look pretty snazzy with a well-affected, if not super high-quality, repaint.

In Part I in our series outlining best practices for scaling observability, we reviewed the data analysis capabilities that can help engineers troubleshoot faster during high pressure situations during a game launch. Nobody wants lag time or crashes in their game launch. Similarly, no one wants terminated sessions or for your gamer customers to log off and play a competitor’s game.

We believe that one of the most powerful capabilities added to the Logz.io Observability Platform in recent months is our new Service Performance Monitoring (SPM) feature set. As you may have seen earlier this year, Logz.io was named a Visionary in the 2022 Gartner® Magic Quadrant(™) for Application Performance Monitoring and Observability. To that end, SPM is a cornerstone for our related solutions.

After months–or potentially, years–of hard work by teams across a gaming enterprise, when the day arrives for a game launch, the last thing your enterprise needs is slowdowns, glitches, outages or poor performance. It’s the death knell for any game, because for your avid gaming customers, there’s always something else (read: a game that isn’t yours) to check out.

Stoking fears about the threat landscape is a popular approach, and one that I don’t particularly care for. Many will tell you that the threat landscape is constantly changing, that threats are getting more complex, and that actors are getting more sophisticated. “The whole world is getting more difficult and scarier, so buy our stuff!” There’s a ton of media sensationalism too, with the popular image of the hacker sitting at a computer, wearing a dark hoodie.

A goal of open-source observability is unifying several different signals to provide the observability everyone wants. It’s always interesting to speak to people on this journey, and how they try to provide it through open-source projects, and the challenges they can face. I was thrilled to host Pranay Prateek on the most recent episode of the OpenObservability Talks podcast.

One of the biggest buzzwords (or really, buzz acronyms) to pop up in the cybersecurity space in recent years is XDR, or, extended detection and response. The term was coined in 2018 by Nir Zuk, CTO and co-founder of Palo Alto Networks. It was posited as a new way to think about security, where data is taken from several platforms and it gets correlated and analyzed.

It’s monitoring time. We all collect metrics from our system and applications to monitor their health, availability and performance. Our metrics are essentially time-series data collected from various endpoints. Then, it is stored in time series specialized databases, and then visualized in the metrics graphs we all know and love.