Operations | Monitoring | ITSM | DevOps | Cloud

Metrics provide visibility into engineering operations, allowing teams to iteratively improve. By tracking key data points like deployment frequency, lead time, server uptime, and change fail rate over time, organizations can spot trends, compare against benchmarks, and address process inefficiencies.

Internal Developer Portals and platforms do a lot—they're an all-in-one system of record, lever for defining and driving best practice, and vehicle for creating new software components. It's not hard to understand why undertaking such a project can be labor and resource intensive. But it doesn't necessarily have to be.

There is nothing more valuable to an organization than data—about customers, products, opportunities, gaps... the list goes on. We know that to maximize value streams for the business we need to turn a critical eye to data related to how each group operates, including software development teams. In 2019 a group known as the DevOps Research and Assessment (DORA) team set out to find a universally applicable framework for doing just that.

Backstage by Spotify is an open-source platform for building IDPs (internal developer portals). IDPs provide standardization and visibility for engineering teams and managers, as the single source of truth for status, ownership, and metrics on software projects. Teams often try Backstage when they have aspirations of “building anything and everything,” but run into problems when supporting “anything and everything” becomes a full-time job for multiple front and back-end engineers.

Lumigo is excited to announce its microservice troubleshooting platform now provides developers and DevOps with the power of OpenTelemetry (OTel) with a single click. Lumigo has long been the leading troubleshooting platform for serverless, but now, users can harness its best-in-class debugging and observability platform for all microservices-based environments.

With the rise of cloud computing, containerization, and microservices architecture, developers are adopting new approaches to building and deploying applications that are more scalable and resilient. Microservices architecture, in particular, has gained significant popularity due to its ability to break down monolithic applications into smaller, independent services.

Reporting from multiple engineering systems is crucial for maintaining the high velocity and quality standards required in today’s tech industry. However, creating reports can be challenging due to the need for deep technical expertise and aggregation of many separate systems worth of data.

From the Regulatory Lead to the Site Reliability Engineers (SREs) and development team, there are quite a few individuals involved in keeping a Financial Technology (FinTech) company compliant. And there are quite a few regulations to stay in line with: anti-money laundering (AML), know your customer (KYC), payment card industry data security standard (PCI DSS), the list goes on.

Engineering teams rely on certain metrics to assess their ability to deliver quality products, on time. This is a useful exercise, but execution has been lacking—with metric collation often handled via spreadsheet, or stand-alone tool. Neither approach is ideal for two reasons: 1) How—or more specifically where—metrics are collected silos them away from business context.

In an article titled The Worst Programmer I Know, Dan North, the creator of behavior-driven development, writes about a nearly fired developer he saved from the unemployment line. This developer consistently delivered zero story points, even though delivered story points was the primary metric for developer productivity at their (unnamed) software consultancy.