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  • Booking.com Doubles Delivery Performance Using DORA Metrics and Micro Frontends

    The team in Booking.com’s fintech business unit implemented a series of improvements across the backend and the frontend of its platform and was able to double the delivery performance, as measured by DORA metrics. Additionally, the Micro Frontends (MFE) pattern was used to break up the monolithic FE application into multiple decomposed apps that could be deployed separately.

  • State of FinOps 2024: Reducing Waste and Embracing AI

    In the 2024 State of FinOps survey, Engineering Enablement has been replaced by a focus on cost and waste reduction. This shows maturity of FinOps as the persona getting the most value from FinOps remains the engineer. The confluence of AI and FinOps observability aims to optimise cloud spend visibility and improve insights into early AI experimentation, as well as sustainability goals.

  • Grafana v10.3: Visualizations, Alerting, Management and Log Analysis Improvements

    Grafana 10.3 introduces a range of enhancements spanning visualization, instance management, alerting, and log analysis. These upgrades include improved tooltips and zoom functionality for data navigation, alongside features for tracking metric changes and visualizing system health. Additionally, improvements in alerting and log analysis are also available.

  • Learning from Big Tech’s Engineering Productivity Metrics

    Gergely Orosz and Abi Noda published a Pragmatic Engineer article titled Measuring Developer Productivity: Real-World Examples. InfoQ reports on insights from Noda’s survey of engineering metrics used across 17 well-known tech giants. Noda found that rather than wholesale adoption of frameworks like DORA, leading teams use a mix of org-specific qualitative and quantitative metrics.

  • Grafana Beyla Provides Auto-Instrumented Observability through eBPF

    Grafana has released Grafana Beyla, an open-source eBPF auto-instrumentation tool for application observability. Beyla is able to report span information and RED metrics (Rate-Errors-Duration) for both Linux HTTP/S and gRPC services. This is accomplished without having to make code modifications for inserting probes.

  • OpenTelemetry Protocol (OTLP) 1.0.0 Released

    Recently, the OpenTelemetry Protocol (OTLP) 1.0.0 was released. OLTP specification describes telemetry data's encoding, transport, and delivery mechanism between telemetry sources, intermediate nodes such as collectors, and telemetry backends. It is a general-purpose telemetry data delivery protocol designed in the scope of the OpenTelemetry project.

  • Grafana Adds Service Accounts and Improves Debugging Experience

    Grafana Labs has released version 9.5 of Grafana including improvements to Grafana Alerting, service accounts, and improvements to the dashboards. Support bundles were also released providing a simpler way to gather and share debugging information about the Grafana stack. AWS has announced support for Grafana 9.4 within their Amazon Managed Grafana service.

  • Effective and Efficient Observability with OpenTelemetry

    Daniel Gomez Blanco, principal engineer at Skyscanner, shared his experiences at QCon London on a large-scale observability initiative at his company, based on adopting OpenTelemetry across hundreds of services and the motivation and value gained from adopting open standards across the entire organization.

  • New CloudWatch Metrics for AWS Lambda Asynchronous Invocations

    AWS recently added three new Amazon CloudWatch metrics for AWS Lambda: AsyncEventsReceived, AsyncEventAge, and AsyncEventsDropped, to monitor the performance of asynchronous event processing.

  • Grafana Tempo Introduces New Query Language and Support for Apache Parquet

    Grafana has released Grafana Tempo 2.0 which introduces the new TraceQL query language and support for the Apache Parquet format. Grafana Tempo is an open-source tracing backend that works with object storage. The new TraceQL query language works with the Apache Parquet format to provide improved search times and queries aligned to traces.

  • Grafana Adds Outlier Detection to Its Machine Learning Toolkit

    Grafana has released outlier detection as part of their Grafana Machine Learning toolkit. Outlier detection can be used to monitor a group of similar things and be alerted when some of them start to behave differently than the norm.

  • Prometheus Adds Long Term Support Model and Improved Remote Write Mode

    Prometheus, the open-source monitoring tool, has added a number of new features including a reduced functionality remote write mode. Additional improvements include a new HTTP service discovery mechanism, native histogram support, additional integrations for Alertmanager, and a new long-term support model.

  • How We Can Use Data to Improve System Quality

    To understand how systems are being used, we can collect metrics and identify trends over time. The data and insights gained can be used to improve system quality by improving software design or testing patterns.

  • Using the Technical Debt Metaphor to Communicate Code Quality

    With technical debt, we end up paying a gradually rising cost. The technical debt metaphor was intended as a way to help us talk and think about the invisibility of decisions and qualities in code. Kevlin Henney gave a keynote about Six Impossible Things at QCon London 2022 and at QCon Plus May 10-20, 2022. His sixth impossibility was technical debt is quantifiable as financial debt.

  • Can MTTR Be an Effective Business Metric?

    In a recent blog post, Sidu Ponnappa shared how MTTR should be a key business metric to measure engineering efficiency. Ponnappa notes that only tracking uptime provides no goals to target for improvements. In a recent talk at SREcon22, Courtney Nash, senior research analyst at Verica, shared that MTTR can misrepresent what is actually happening during incidents and can be an unreliable metric.

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