February 2022 Summaries

Go 1.18 is set to be one of the most exciting releases since Go 1.0, with significant improvements in profiling. The CPU profiler for Linux has become more accurate, addressing issues related to dropped POSIX signals and signal generation. Profiler label bug fixes have also been implemented, improving the accuracy of stack traces. These enhancements aim to provide better insights into program performance and improve overall profiling capabilities.

The latest release of Go, version 1.18, promises to be one of the most exciting releases since its inception, with several major features and improvements in profiling. The CPU profiler for Linux has become more accurate, particularly on multi-core systems, thanks to a change that addresses issues with signal generation and delivery. Additionally, there are improvements to profiler labels, which allow users to associate arbitrary key-value pairs with the currently running goroutine, and these labels now end up in CPU and goroutine profiles. There is also a fix for stack trace bug fixes, including a regression involving inlined closures that was fixed by Than McIntosh. These changes aim to improve profiling accuracy and reliability, making Go 1.18 a significant update for developers.

Datadog Cloud Security Posture Management (CSPM) offers organizations a comprehensive solution for managing governance, risk, and compliance (GRC) in cloud environments, specifically expanding its services to include Microsoft Azure. By providing a centralized platform, Datadog CSPM enables users to track their compliance posture, automate audit evidence collection, and identify misconfigurations across multi-cloud infrastructures. The platform supports industry-standard frameworks such as PCI DSS, SOC 2, GDPR, HIPAA, and CIS, ensuring that cloud environments adhere to the latest standards. Datadog's CSPM features a security posture dashboard that offers high-level overviews and detailed compliance reports, allowing organizations to prioritize and address critical violations effectively. It runs over 250 security and compliance rules to detect deviations from compliance controls and generates detailed findings with contextual infrastructure data to facilitate issue resolution. Additionally, CSPM integrates into the broader Datadog Cloud Security Platform, allowing users to correlate findings with other security issues and build collaborative dashboards, enhancing visibility and collaboration among engineering and GRC teams.

Datadog has introduced an improved Notebooks feature that enables teams to create and manage key reports and documentation for their infrastructure. The new Notebooks landing page allows users to create, access, and standardize notebooks using templates, improving search capabilities, and enabling view-only browsing. This update aims to enhance the quality of internal documentation and streamline monitoring and troubleshooting efforts across teams.

Datadog has introduced a new Notebooks landing page that allows teams to create and access standardized notebooks from a single place, enabling them to create and manage key reports and documentation as they build out, monitor, and maintain their infrastructure. The new features include creating and saving notebooks with out-of-the-box and custom templates, easily navigating notebooks with improved search features, and browsing notebooks without leaving a trace. Templating allows teams to standardize their documentation by providing a template gallery of postmortems, RFCs, runbooks, and more, enabling them to wireframe documentation procedures for use across the organization. The new search features enable team members to quickly gather relevant information as they monitor applications and respond to incidents, while browsing without leaving a trace ensures that notebooks remain high-quality and easy to navigate.

Datadog has launched a new Notebooks landing page that enables teams to create and manage standardized notebooks for infrastructure monitoring and maintenance. The new feature allows users to create and save notebooks with out-of-the-box and custom templates, navigate their notebooks with improved search features, browse notebooks without leaving a trace, and standardize their documentation by providing a template gallery of postmortems, RFCs, runbooks, and more. Templating enables teams to wireframe documentation procedures for use across the organization, while typing allows users to keep their documentation organized and easily find specific notebooks in the future. The new feature is tightly integrated with Datadog Incident Management, allowing seamless pivoting from viewing incident data to documenting it in postmortems.

MongoDB Atlas for Government is a fully managed cloud database service designed to meet stringent security and compliance requirements for US federal agencies and state, local, and education (SLED) entities. It has achieved FedRAMP Ready and FedRAMP In-Process designations and can be deployed in AWS GovCloud. Datadog for Government now integrates with Atlas for Government, allowing users to monitor the health and performance of their database clusters alongside other infrastructure telemetry data. This integration enables monitoring key metrics like throughput, latency, and resource utilization, as well as creating custom dashboards and setting up automated alerts. With this combination, US federal agencies and SLED entities can modernize their legacy systems while complying with strict regulations.

The text discusses how advanced log analytics can be used to uncover patterns and insights in data. It highlights the use of formulas and functions in Datadog Log Management to answer complex questions, such as whether a system is behaving abnormally, how its behavior changes over time, the usage and performance breakdown of an application, and any seasonal patterns in its usage. The text also provides examples of how these techniques can be applied to various scenarios, including code deployment impact analysis, revenue tracking, geographical user base breakdown, service request latency comparison, and identifying seasonal trends in application use.

Datadog Log Management allows users to centralize their log data and perform advanced analytics on it. Users can use formulas and functions to manipulate and analyze their logs, enabling them to answer complex questions such as whether a system is behaving abnormally, how its behavior changes over time, what the usage and performance breakdown of an application is, and if there are seasonal patterns in how an application is used. By applying these formulas and functions, users can gain valuable insights into their infrastructure, applications, and business operations, and make data-driven decisions to optimize their systems and improve their end-user experience.

MongoDB Atlas is a fully managed cloud database service for modern applications. The MongoDB team has released a dedicated environment, Atlas for Government, which supports US federal agencies and state, local, and education entities that need to meet stringent security and compliance requirements. This environment can be deployed in AWS GovCloud, allowing organizations already operating in this environment to quickly get up and running with the robust database platform. The Atlas for Government integration now comes with a Datadog integration, giving users a safe and secure way to monitor the health and performance of their database clusters alongside the rest of their infrastructure telemetry. With the Datadog integration, users can view key database metrics, clone and customize dashboards, set up automated alerts, and improve the reliability of their services while complying with strict regulations.

Product designers at Datadog use their own platform's Real User Monitoring (RUM), logs and notebooks to gather quantitative user data for improving the user experience of their products. They shared three examples where this approach was effective: 1) Picking a monospace font by tracking which one users were seeing most frequently, 2) Updating the DraggablePane component based on usage data, and 3) Expanding input syntax for custom time frames using user-entered text strings. The use of Datadog's own tools allowed for efficient collaboration and analysis across teams.

Won Choi and the team at Datadog are using their own product to gather user experience data, a practice called "dogfooding", to improve the platform. They used Datadog's Real User Monitoring (RUM) tool to collect quantitative data on how users interact with certain features of the platform. By analyzing this data, they made informed design decisions and improved the user experience. The team tracked data on three specific projects: updating the monospace font used in the app, simplifying a complex UI component, and adding custom time frames to a date picker component. They found that using their own product helped them gain insights into user behavior and make data-backed design decisions. By sharing their findings with the team and documenting their process, they promoted collaboration and efficiency within the product design team.

The guide discusses the importance of securing Kubernetes applications and provides best practices for mitigating common security risks at each layer of the infrastructure. It highlights the need for a defense-in-depth strategy, which involves implementing security controls across multiple layers to protect against various types of threats. The guide covers application code and third-party dependencies, container images and workloads, Kubernetes clusters and pods, and cloud infrastructure hosting the application. It also explores how Datadog's Security Platform can help with end-to-end visibility into Kubernetes environments and provides tools for monitoring security risks, detecting attacks, and streamlining application security. The guide emphasizes the importance of regular audits, limiting access to sensitive resources, and using the principle of least privilege for cloud accounts. Additionally, it discusses securing Kubernetes infrastructure in the cloud by enabling audit logging, restricting access to provider metadata APIs, and implementing a multi-layered approach to security.

Many organizations use AWS to build event-driven applications, utilizing services like AWS Lambda to enhance performance and scalability by processing requests between resources such as Amazon API Gateway and Amazon Kinesis. Datadog has expanded its serverless monitoring capabilities to provide detailed tracing and real-time insights for AWS managed services interacting with Python and Node.js Lambda functions, including services like SQS, SNS, and DynamoDB. This enhancement allows users to detect and address latency and errors, visualize service relationships, and correlate traces with performance metrics for comprehensive visibility and troubleshooting. By enabling quick identification of performance issues within serverless architectures, Datadog enhances users' ability to resolve problems and optimize configurations, thus improving application performance and reducing costs. Users can also leverage the new trace map and Trace Analytics to monitor and verify performance improvements after changes, with the option to sign up for a free trial for further exploration of Datadog's capabilities.

Datadog has announced the acquisition of CoScreen, a real-time collaboration platform designed to enhance remote work experiences. CoScreen's unique approach allows users to share applications and windows in a secure, shared workspace, enabling seamless collaboration among distributed teams. The integration of CoScreen into Datadog aims to improve incident response, troubleshooting, and mean time to resolution (MTTR) for customers. Existing CoScreen users can continue using the platform during the integration process, while new users will be able to sign up once it is complete.

The Datadog Spotlight Series features interviews with dedicated team members from around the globe, highlighting their journeys and experiences within the company. In this installment, Egli Hamitaj, a Technical Account Manager (TAM) based in Amsterdam, shares his insights on life as a TAM at Datadog. Hamitaj discusses his transition to the role, the impact of TAMs on customers, and his favorite aspects of the job. He also reflects on the support he received from colleagues during the COVID-19 lockdown when joining Datadog remotely. The company is currently hiring for various roles within their Post-Sales team in the Technical Solutions department.

Here is a one-paragraph summary of the text: Egli Hamitaj, a Technical Account Manager at Datadog's Amsterdam office, discusses his journey to his current role and how it impacts the company's customers. As part of the Post-Sales team, Egli works closely with customers to help them maximize their use of the Datadog platform, while also serving as an internal advocate for customer needs and collaborating with other teams to drive product evolution. He shares that his favorite part of the role is seeing customers implement tailored observability strategies and being part of the process, and highlights the supportive team environment he experienced during his onboarding, particularly during the COVID-19 lockdown. Egli's enthusiasm for Datadog and its products is evident throughout the conversation, showcasing his passion for helping customers achieve their observability goals.

Datadog is integrating CoScreen, a real-time collaboration platform, to help teams detect, troubleshoot, and resolve issues in their applications and infrastructure. CoScreen offers a unique collaboration experience that allows users to work together seamlessly, eliminating the need for formal video conferencing tools. The integration aims to facilitate incident response, speed up troubleshooting, and reduce mean time to resolution (MTTR), making it easier for teams to collaborate and streamline their processes.

Agentil's SAP NetWeaver integration is now available on the Datadog Marketplace, allowing users to monitor their entire fleet of SAP NetWeaver systems and visualize telemetry data alongside other integrations. The integration provides two out-of-the-box dashboards: SAP Global Overview for a high-level view of system health and performance, and SAP NetWeaver System for in-depth analysis of individual systems. Users can also set up monitors to alert them of transactional and queued RFC errors, as well as increased dialog response time, which may indicate performance issues or overloaded systems. The integration is available for a free trial and can be accessed through the Datadog Marketplace.

Agentil has announced that its SAP NetWeaver integration is now available on the Datadog Marketplace. This integration allows users to visualize and analyze SAP NetWeaver telemetry data alongside other integrations, enabling them to detect and troubleshoot issues more easily. The integration provides two out-of-the-box dashboards, one for a high-level overview of all SAP NetWeaver systems and another for in-depth analysis of system performance issues. It also includes features such as alerts on transactional and queued RFC errors, troubleshooting of increased dialog response time, and correlation with other components like SAP HANA. The integration is now available to users on the Datadog Marketplace, where it can be easily installed and configured.

Sourcegraph is a universal code search tool that helps developers navigate and understand their codebase across multiple repositories. Its latest extension, datadog-service-map, integrates with Datadog APM to provide insights into service dependencies and performance metrics within the code search workflow. This allows developers to easily locate impacted services, fix bugs, and apply changes across their entire codebase. The extension also enables seamless pivoting between Sourcegraph and Datadog APM for visual representation of application topology and real-time updates on service endpoints.

The `datadog-service-map` Sourcegraph extension brings Datadog APM's knowledge of service dependencies to code search workflows, enabling users to visualize and understand the relationships between services in their applications. This extension allows users to see which other services are making calls to a given service, pivot seamlessly to Datadog APM for additional context, and identify potential issues such as increasing errors or latency. It also helps users ensure API calls hit the right endpoints by identifying downstream services and verifying requests are hitting the correct endpoint. By using this extension together with Sourcegraph and Datadog APM, developers can navigate their entire codebase to fix issues quickly and precisely.

Lucas Masson discusses the challenges of securing modern production systems, emphasizing the need for comprehensive security measures amid the complexities of distributed systems and microservices. The introduction of Datadog Application Security Management (ASM) aims to address these challenges by providing integrated security solutions within the Cloud Security Platform. ASM enables teams to receive alerts on significant threats, identify authenticated attackers, assess the impact of attacks, and gain code-level insights for remediation. It offers coverage for various vulnerabilities, including SQL injections and cross-site scripting, and facilitates a unified view of attack vectors across the stack, enhancing collaboration between security and engineering teams. The ASM system is designed to be easily integrated with existing Datadog services, allowing users to quickly implement it without additional agents or traffic redirection.

Datadog has introduced App and API Protection (AAP) as an enhancement to its Security Platform, designed to secure modern production systems against sophisticated threats. AAP enables security, operations, and development teams to collaborate effectively in building secure applications by providing real-time alerts for threats targeting business logic, identifying authenticated malicious actors, and offering insights for remediation through code-level visibility. The platform covers a wide range of vulnerabilities, including OWASP Top 10 attacks like SSRF and SQL injections, and plans to expand further. AAP's integration with Datadog's existing monitoring tools allows for seamless implementation without additional deployment requirements, offering a comprehensive view of the entire attack surface by unifying application, API, and infrastructure security management. This integration helps teams quickly assess the impact of attacks and respond effectively, ensuring robust protection for customer data and company infrastructure.

Ruby, celebrated for its simple syntax, powers the Ruby on Rails framework, and now benefits from Datadog's Continuous Profiler, which is generally available for Ruby applications. This tool provides low-overhead, code-level performance insights, allowing developers to view resource usage of individual Ruby methods, correlate profiles and distributed traces, and compare profiles across different dimensions. As Ruby applications grow, identifying bottlenecks becomes more challenging, but the Continuous Profiler automatically collects stack traces and visualizes them in flame graphs to highlight resource consumption. It integrates with Datadog APM for end-to-end distributed tracing, enabling developers to uncover potential bottlenecks by examining traces with errors or high latency. The profiler supports performance verification by comparing profiles from different versions, particularly useful for canary releases, and allows performance comparisons across environments using Datadog tags. Additionally, Continuous Profiler is available for Java, Python, and Go, with support for more languages in development, and Datadog offers a 14-day free trial for new users.