Operations | Monitoring | ITSM | DevOps | Cloud

Forethought is a leading AI company providing customer service solutions that transform the customer experience. As a high-growth startup with a fast-expanding engineering org., teams had to deal with compounding complexity, leading to challenges measuring the impact and health of their services. Forethought’s core engineering team maintains common services between other internal teams, infrastructure, data, and tools and, as they added more engineers, the original team split into five.

We recently partnered with GameCI to bridge the gap between CircleCI and the game development scene. This partnership brought forth the Unity orb, a reusable component of config you can plug into your CircleCI configuration file to build and test your Unity projects. For a while now, continuous integration and delivery have been part of the software development cookbook of several software houses and IT departments. However, this is often not the case in game development.

Recently, technology roles have become more generalized—cloud computing, for instance, requires a broader knowledge of technologies like storage and network. As technology has continued to evolve over the decades, many job positions have blurred into many roles or even morphed into new roles with new responsibilities.

A recent Honeywell survey reinforced something many in the MSP world already knew: data centers need managed service providers. 96% of facility managers indicated remote management is important, but only 34% had remote management capabilities in place. That’s surprising in a digital world where data centers enable critical business functions and an epic business opportunity for MSPs looking to enter the data center world.

To improve reliability, we need to measure it, and to measure it we use SLOs (Service Level Objectives). Or at least, that’s what Google SRE has popularized. In practice, it can be difficult and time-consuming to identify the right things to measure, to get to the right data, and to surface the results in a way that engages the stakeholders and teams involved. And all this is especially hard as we scale our teams and applications across multiple technology stacks.

Welcome back to our monthly product updates - SigNal! So happy to share with everyone that we were trending on the first page of Hacker news over the weekend, and the whole team was so upbeat about it. Last month, we shipped a lot of dashboard and documentation improvements to make SigNoz better for our users. We also participated in conferences, gave talks on open source, and sipped a lot of coffee! Let us see what humans of SigNoz were up to in the month of September 2022!

One of Icinga’s greatest strengths is its ability to integrate with other systems and use those systems’ data to enrich monitoring. It can write time-series data to InfluxDB, Graphite or even Prometheus with our icinga2-exporter. It can talk to different data sources so that hosts and services can be created and managed automatically. This means that lots of manual work is eliminated.

From its inception as a powerhouse for logging, Elastic Observability has grown into a comprehensive solution for full-stack multi and hybrid-cloud observability. Given the increasing complexity of the cloud-native world, the major challenge for observability is twofold: getting deeper and more frictionless visibility at all levels of applications, services, and infrastructure, and making sense of the overwhelming amount of data that is available.

The Cambridge English Dictionary defines a silo as “a part of a company, organization, or system that does not communicate with, understand, or work well with other parts.” Siloing can exist at various organizational levels: siloed departments, siloed teams within a department, and even siloed engineers within a team. In any industry, siloing can cause issues with alignment, communications, and overall delivery, but in fintech, there are additional risks.

Debugging is an unavoidable part of software development, especially in production. You can often find yourself in “debugging hell,” where an enormous amount of debugging consumes all your time and keeps the project from progressing. According to a report by the University of Cambridge, programmers spend almost 50% of their time debugging. So how can we make production debugging more effective and less time-consuming?