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This article is the first in a multi-part series sharing a breadth of Analytics Engineering work at Netflix, recently presented as part of our annual internal Analytics Engineering conference. Subsequent posts will detail examples of exciting analytic engineering domain applications and aspects of the technical craft.
Our ecosystem enables engineering teams to run applications and services at scale, utilizing a mix of open-source and proprietary solutions. One crucial way in which we do this is through the democratization of highly curated data sources that sunshine usage and cost patterns across Netflixs services and teams.
Monitoring MySQL databases is essential for maintaining performance, detecting issues early, and ensuring efficient resource use by tracking critical metrics. These tools offer real-time analytics, advanced visualization, customizable alerts, and scalability. This ensures notifications about issues relevant to your environment.
That is, traces, logs, and metrics, which gave us the information to make our systems observable. For example, an organization might have App A send metrics to SaaS Tool X, and traces and logs to SaaS Tool Y. App B sends traces to SaaS Tool J, logs to SaaS Tool L, and metrics to self-hosted Tool M. Consider some examples.
The Dynatrace platform now enables comprehensive data exploration and interactive analytics across data sets (trace, logs, events, and metrics)empowering you to solve complex use cases, handle any observability scenario, and gain unprecedented visibility into your systems.
Kafka is optimized for high-throughput event streaming , excelling in real-time analytics and large-scale data ingestion. RabbitMQ is an open-source message broker that supports multiple messaging protocols , including AMQP, STOMP, MQTT, and RabbitMQ Streams. What is RabbitMQ? What is Apache Kafka?
” Don’t forget metrics and other telemetry signals Although we’re focusing here on logs and traces, metrics and other telemetry data are also essential for observability and deeper context. Explore Distributed Tracing and Log Management and Analytics , complete with prepopulated data in the Dynatrace Playground.
However, when working with Kubernetes, its distributed and ephemeral nature means that logs are scattered across multiple nodes and pods, making it difficult to ensure that all logs are preserved, easily accessible, and enriched with necessary context for future analytics. Flexibly choose the level of observability you need.
Amazon Bedrock , equipped with Dynatrace Davis AI and LLM observability , gives you end-to-end insight into the Generative AI stack, from code-level visibility and performance metrics to GenAI-specific guardrails. Send unified data to Dynatrace for analysis alongside your logs, metrics, and traces.
While RAG leverages nearest neighbor metrics based on the relative similarity of texts, graphs allow for better recall of less intuitive connections. The popular opensource libraries and most of the vendor solutions promote a general notion that the “graph” in GraphRAG gets generated automatically by an LLM.
Customizable reports and metrics for tracking testing progress. Kiwi TCMS Kiwi TCMS is an open-source test management tool for both manual and automated tests. Squash TM Squash TM is an open-source, web-based test management tool. Real-time analytics and reporting for monitoring test execution and results.
Kiwi TCMS Fully open-source with no limitations on users or test cases. A valuable alternative for teams looking for a cost-effective, open-source solution that goes beyond basic test case management. The open-source edition is ideal for smaller teams, with the flexibility to upgrade to enterprise features.
TestLink is an open-source test management tool that allows you to perform and manage the entire software testing lifecycle. Reporting & Analysis: Test metrics and reporting capabilities are there to track the testing process and find areas for improvement. What is Testlink? QA teams can collaborate on managing tests.
Many of these tools are opensource. Clear Reports and Analytics: Teams get to see which tests passed or failed and how testing is going. Teams can monitor progress and important quality metrics effortlessly. It is open-source and free to use. Pros Free and open-source.
The AWS + F1 partnership is a great example of leveraging AI and analytics to process large volumes of data and real-time streams, leading to continuous improvement and strategic decision-making in a highly competitive environment. Finally, always frame your metrics in terms of business value.
More services from increasing vendors and open-source projects also expand the attack surface through vulnerabilities and attack vectors. With access to full Kubernetes logs, metrics, and trace data in a causal data lakehouse , teams can detect vulnerable instances and surface signs of compromise for quick remediation.
The release candidate of OpenTelemetry metrics was announced earlier this year at Kubecon in Valencia, Spain. Since then, organizations have embraced OTLP as an all-in-one protocol for observability signals, including metrics, traces, and logs, which will also gain Dynatrace support in early 2023.
In IT and cloud computing, observability is the ability to measure a system’s current state based on the data it generates, such as logs, metrics, and traces. Organizations usually implement observability using a combination of instrumentation methods including open-source instrumentation tools, such as OpenTelemetry.
As businesses increasingly embrace these technologies, integrating IoT metrics with advanced observability solutions like Dynatrace becomes essential to gaining additional business value through end-to-end observability. Both methods allow you to ingest and process raw data and metrics.
The complexity of such deployments has accelerated with the adoption of emerging, open-source technologies that generate telemetry data, which is exploding in terms of volume, speed, and cardinality. Dynatrace extends its unique topology-based analytics and AIOps approach.
This year I wrote two open-source apps for Dynatrace users. Agentless RUM, OpenKit, and Metric ingest to the rescue! Now we have performance and errors all covered: Business Analytics. What insights can we gain from usage metrics that we can feed-back to our product management teams? Dynatrace news.
The only way to address these challenges is through observability data — logs, metrics, and traces. IT pros want a data and analytics solution that doesn’t require tradeoffs between speed, scale, and cost. The next frontier: Data and analytics-centric software intelligence. Enter Grail-powered data and analytics.
With 99% of organizations using multicloud environments , effectively monitoring cloud operations with AI-driven analytics and automation is critical. IT operations analytics (ITOA) with artificial intelligence (AI) capabilities supports faster cloud deployment of digital products and services and trusted business insights.
Welcome back to the second part of our blog series on how easy it is to get enterprise-grade observability at scale in Dynatrace for your OpenTelemetry custom metrics. In Part 1 , we announced our new OpenTelemetry custom-metric exporters that provide the broadest language coverage on the market, including Go , .NET record(value); }.
In Part 1 we explored how you can use the Davis AI to analyze your StatsD metrics. In Part 2 we showed how you can run multidimensional analysis for external metrics that are ingested via the OneAgent Metric API. In Part 3 we discussed how the Davis AI can analyze your metrics from scripting languages like Bash or PowerShell.
The short answer: The three pillars of observability—logs, metrics, and traces—converging on a data lakehouse. Grail combines the big-data storage of a data warehouse with the analytical flexibility of a data lake. With Grail, we have reinvented analytics for converged observability and security data,” Greifeneder says.
Manual and configuration-heavy approaches to putting telemetry data into context and connecting metrics, traces, and logs simply don’t scale. By unifying log analytics with PurePath tracing, Dynatrace is now able to automatically connect monitored logs with PurePath distributed traces. New to Dynatrace? Start your free trial!
OpenTelemetry metrics are useful for augmenting the fully automatic observability that can be achieved with Dynatrace OneAgent. OpenTelemetry metrics add domain specific data such as business KPIs and license relevant consumption details. Enterprise-grade observability for custom OpenTelemetry metrics from AWS. Dynatrace news.
To ensure observability, the opensource CNCF project OpenTelemetry aims at providing a standardized, vendor-neutral way of pre-instrumenting libraries and platforms and annotating UserLAnd code. New OpenTelemetry metrics exporters provide the broadest language support on the market.
Over the last year, Dynatrace extended its AI-powered log monitoring capabilities by providing support for all log data sources. We added monitoring and analytics for log streams from Kubernetes and multicloud platforms like AWS, GCP, and Azure, as well as the most widely used open-source log data frameworks.
With siloed data sources, heterogeneous data types—including metrics, traces, logs, user behavior, business events, vulnerabilities, threats, lifecycle events, and more—and increasing tool sprawl, it’s next to impossible to offer users real-time access to data in a unified, contextualized view. Understanding the context.
Fluentd is an open-source data collector that unifies log collection, processing, and consumption. Output plugins deliver logs to storage solutions, analytics tools, and observability platforms like Dynatrace. All metrics, traces, and real user data are also surfaced in the context of specific events. Dynatrace news.
That is, relying on metrics, logs, and traces to understand what software is doing and where it’s running into snags. OpenTelemetry, the opensource observability tool, has emerged as an industry-standard solution for instrumenting application telemetry data to make it observable. What is OpenTelemetry?
Open-sourcemetricsources automatically map to our Smartscape model for AI analytics. We’ve just enhanced Dynatrace OneAgent with an openmetric API. Davis AI analyzes your StatsD metrics. In addition, Dynatrace fully integrates these metrics into Smartscape. Dynatrace news.
Because of its flexibility, this opensource approach to instrumenting and collecting telemetry data is becoming increasingly important in large-size organizations. Before OpenTelemetry and the W3C Trace Context open standard that underpins it, observability vendors had to reverse-engineer tracing libraries.
In this blog post, we’ll use Dynatrace Security Analytics to go threat hunting, bringing together logs, traces, metrics, and, crucially, threat alerts. Dynatrace Grail is a data lakehouse that provides context-rich analytics capabilities for observability, security, and business data.
TiDB is an open-source, distributed SQL database that supports Hybrid Transactional/Analytical Processing (HTAP) workloads. It's challenging to troubleshoot issues in a distributed database because the information about the system is scattered in different machines. Before version 4.0,
Dynatrace has supported the OpenTelemetry project for years as a key contributor and contributed to its rise to a popular opensource observability framework for cloud-native software. Many global enterprises have instrumented their code to emit traces, metrics, and logs in a standardized and vendor-neutral way using OpenTelemetry.
Grafana, a leading open-source platform for monitoring and observability, has emerged as a critical player in enhancing security postures through real-time security analytics and alerts. Businesses are in dire need of robust tools that not only detect threats in real time but also provide actionable insights to mitigate risks.
Monitor your cloud OpenPipeline ™ is the Dynatrace platform data-handling solution designed to seamlessly ingest and process data from any source, regardless of scale or format. With OpenPipeline, you can effortlessly collect data from Dynatrace OneAgent ® , open-source collectors such as OpenTelemetry, or other third-party tools.
OpenTelemetry has become a standard for collecting traces, metrics, and logs. OpenLLMetry, an opensource SDK built on OpenTelemetry, offers standardized data collection for AI Model observability. OpenLLMetry provides an opensource SDK for LLM observability, seamlessly integrating with Dynatrace for in-depth analysis.
Every service and component exposes observability data (metrics, logs, and traces) that contains crucial information to drive digital businesses. To connect these siloes, and to make sense out of it requires massive manual efforts including code changes and maintenance, heavy integrations, or working with multiple analytics tools.
These technologies are poorly suited to address the needs of modern enterprises—getting real value from data beyond isolated metrics. Grail needs to support security data as well as business analytics data and use cases. This decoupling ensures the openness of data and storage formats, while also preserving data in context.
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