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Why is duplicating a case document important? The post Duplicate cases: A game-changer for Security Investigator productivity and efficiency appeared first on Dynatrace news. Dynatrace introduces the next great addition to collaborative features for security investigators. You can now duplicate cases in Security Investigator.
In this blog, well explore a structured approach to system design using a proven template that can help engineers, architects, and teams craft efficient, high-performing systems.
A good Kubernetes SLO strategy helps teams manage and make containerized workloads more efficient. Efficient coordination of resource usage, requests, and allocation is critical. As every container has defined requests for CPU and memory, these indicators are well-suited for efficiency monitoring.
Costs and their origin are transparent, and teams are fully accountable for the efficient usage of cloud resources. Our comprehensive suite of tools ensures that you can extract maximum value from your billing data, efficiently turning insights into action. Figure 4: Set up an anomaly detector for peak cost events.
Then, document the specifics of your desired end state. You also need to focus on the user experience so that future toolchains are efficient, easy to use, and provide meaningful and relevant experiences to all team members. Modernizing your technology stack will improve efficiency and save the organization money over time.
Fast and efficient log analysis is critical in todays data-driven IT environments. For enterprises managing complex systems and vast datasets using traditional log management tools, finding specific log entries quickly and efficiently can feel like searching for a needle in a haystack.
In this blog post, we will see how Dynatrace harnesses the power of observability and analytics to tailor a new experience to easily extend to the left, allowing developers to solve issues faster, build more efficient software, and ultimately improve developer experience!
A Dynatrace API token with the following permissions: Ingest OpenTelemetry traces ( openTelemetryTrace.ingest ) Ingest metrics ( metrics.ingest ) Ingest logs ( logs.ingest ) To set up the token, see Dynatrace API – Tokens and authentication in Dynatrace documentation. You can even walk through the same example above.
Adding Dynatrace runtime context to security findings allows smarter prioritization, helps reduce the noise from alerts, and focuses your DevSecOps teams on efficiently remedying the critical issues affecting your production environments and applications. This increases the number of findings to prioritize.
However, not many realize the efficiencies they can gain when data from all customer experience processes – observability, customer behavior, and business data – is in a single place, as it is with the Dynatrace Grail data lakehouse. Additionally, existing customers tend to spend 67% more on average than new customers.
Ingested events are stored in the semantic dictionary , which allows you to efficiently visualize, analyze, and automate the orchestration of security findings in a unified and product-independent way. In addition, with runtime entity contextualization , security findings can be mapped to monitored entities.
How To Automate Documentation Workflow For Developers. How To Automate Documentation Workflow For Developers. Why Should You Care About High-Quality Documentation? Many teams struggle with writing documentation. Many teams struggle with writing documentation. Automating Documentation From a High Level.
The following figure depicts imaginary “evolution” of the major NoSQL system families, namely, Key-Value stores, BigTable-style databases, Document databases, Full Text Search Engines, and Graph databases: NoSQL Data Models. Document databases advance the BigTable model offering two significant improvements. 2) Aggregates.
We are updating product documentation to include underlying static assumptions. The FinOps Foundation includes sustainability in its framework, stating, FinOps and cloud sustainability mutually support each other through a similar approach to conscientious and responsible technology usage that enables workload efficiency.
It also facilitates access to data in the view through OGNL expressions, enabling developers to retrieve stored data efficiently. Looking at the frameworks documentation, we’re unable to find any reference to such a keyword. Unlike a standard stack, it acts as an intermediary for the objects it contains.
Your companys AI assistant confidently tells a customer its processed their urgent withdrawal requestexcept it hasnt, because it misinterpreted the API documentation. These are systems that engage in conversations and integrate with APIs but dont create stand-alone content like emails, presentations, or documents.
The complexity and numerous moving parts of Kubernetes multicloud clusters mean that when monitoring the health of these clusters—which is critical for ensuring reliable and efficient operation of the application—platform engineers often find themselves without an easy and efficient solution. Want to try it for yourself?
It allows users to choose between different counting modes, such as Best-Effort or Eventually Consistent , while considering the documented trade-offs of each option. Without an efficient data retention strategy, this approach may struggle to scale effectively. Let’s take a closer look at the structure and functionality of the API.
Incremental Backups: Speeds up recovery and makes data management more efficient for active databases. Performance Optimizations PostgreSQL 17 significantly improves performance, query handling, and database management, making it more efficient for high-demand systems. JSON_VALUE retrieves individual values from JSON documents.
Kafka scales efficiently for large data workloads, while RabbitMQ provides strong message durability and precise control over message delivery. Message brokers handle validation, routing, storage, and delivery, ensuring efficient and reliable communication. This allows Kafka clusters to handle high-throughput workloads efficiently.
Scale with confidence: Leverage AI for instant insights and preventive operations Using Dynatrace, Operations, SRE, and DevOps teams can scale efficiently while maintaining software quality and ensuring security and reliability. Easily set up automated remediation with the new Simple Workflows.
Rising consumer expectations for transparency and control over their data, combined with increasing data volumes, contribute to the importance of swift and efficient management of privacy rights requests. How can this services administrator meet this request in a quick, compliant, and efficient way?
Navigating investigations and threat hunting can involve saving executed queries and found evidence in unstructured text documents that can quickly lose their context. You can see in a structured way how you reached your conclusions without needing to manually document the investigation flow.
Stay ahead of the curve with the OS Services extension for monitored hosts The new Dynatrace OS Services monitoring capability for Windows and Linux hosts (Systemd is required) ensures that your systems run efficiently and potential problems are addressed as soon as they arise. For full details, see Dynatrace Documentation.
For more information, you can always check our documentation. Monitoring average memory usage per host helps optimize performance and manage resources efficiently. Not only can you select a metric, but you can also add multiple filters, use sorting, or directly apply calculations like average or sum.
Their job is to find out the root cause of any SLO violations, ensure visibility into the application landscape to fix problems efficiently and minimize production costs by reducing errors. Follow the instructions available in Dynatrace documentation to allow proper access and configure Firehose settings.
EdgeConnect facilitates seamless interaction, ensuring data security and operational efficiency. In this hybrid world, IT and business processes often span across a blend of on-premises and SaaS systems, making standardization and automation necessary for efficiency.
By leveraging Dynatrace observability on Red Hat OpenShift running on Linux, you can accelerate modernization to hybrid cloud and increase operational efficiencies with greater visibility across the full stack from hardware through application processes. Dynatrace observability is available for Red Hat OpenShift on IBM Power.
To filter findings efficiently, use numerical thresholds like DSS (Dynatrace Security Score) or CVSS (Common Vulnerability Scoring System). Please see the instructions in Dynatrace Documentation. Search full vulnerability descriptions for pinpoint accuracy. Not a Dynatrace customer yet?
Dynatrace released Cloud Native Full Stack injection with a short list of temporary limitations — referenced in our documentation — which don’t apply to Classic Full Stack injection. First, go to the Monitor Kubernetes / OpenShift page in the Dynatrace web UI, as documented in help, and generate a deployment file (see the example below).
The combination of our broad platform with powerful, explainable AI-assistance and automation helps our customers reduce wasted motions and accelerate better business outcomes – whether that’s speed and quality of innovation for IT, automation, and efficiency for DevOps, or optimization and consistency of user experiences.
Whether it’s the speed and quality of innovation for IT, automation and efficiency for DevOps, or enhancement and consistency of user experiences, Dynatrace makes it easy. as part of a larger research document and should be evaluated in the context of the entire document. Gartner Disclaimers.
By following these best practices, you can ensure efficient and safe data management, allowing you to focus on extracting value from Dynatrace while maintaining smooth and compliant business operations. Check our Privacy Rights documentation to stay tuned to our continuous improvements. Get started New to Dynatrace?
Vulnerable function monitoring Tracking vulnerable open source software components efficiently is one of the most important pillars of managing attack surfaces. Figure 3: Spring Framework architecture (source: Spring Framework documentation ) The Spring Framework has many components that offer different functionalities.
There are several limitations to store and fetch such data (all restrictions could be found in official documentation ). One day I faced the problem with downloading a relatively large binary data file from PostgreSQL. To resolve the problem it was suggested to find more suitable data storage.
Today, the composable nature of code enables skilled IT teams to create and customize automated solutions capable of improving efficiency. Minimize overall documentation. Over-documentation reintroduces this issue and can lead to environments and configuration data being out of sync. Address monitoring at scale.
It provides simple APIs for creating indices, indexing or searching documents, which makes it easy to integrate. Mapping is used to define how documents and their fields are supposed to be stored and indexed. All the assets of a specific type use the specific index defined for that asset type to create or update the asset document.
The OpenTelemetry Protocol (OTLP) plays a critical role in this framework by standardizing how systems format and transport telemetry data, ensuring that data is interoperable and transmitted efficiently. OpenTelemetry provides [extensive documentation]([link] and examples to help you fine-tune your configuration for maximum effectiveness.
In this article, we’ll explore these challenges in detail and introduce Keptn, an open source project that addresses these issues, enhancing Kubernetes observability for smoother and more efficient deployments. Insufficient CPU and memory allocation to pods can lead to resource contention and stop Pods from being created.
The DevOps playbook has proven its value for many organizations by improving software development agility, efficiency, and speed. This method known as GitOps would also boost the speed and efficiency of practicing DevOps organizations. GitOps practices can improve infrastructure management efficiency and stability.
Our container logs didn’t contain any valuable root-cause information, and digging through a whole lot of events in our Kubernetes cluster was not a great efficient option either (we would have found the information we were looking for, but the event log is unfiltered and it would have cost a lot of time to dig through it).
Moreover, seamless integration is achieved through out-of-the-box solutions that connect, transform, and map your findings data into a unified format using the Dynatrace Semantic Dictionary, ensuring a smooth and efficient security workflow. In-depth analysis of security findings using tools like Notebooks and Security Investigator.
Here’s a simple rough sketch of RAG: Start with a collection of documents about a domain. Split each document into chunks. This latter approach with node embeddings can be more robust and potentially more efficient. One more embellishment is to use a graph neural network (GNN) trained on the documents.
Using a FaaS model makes it possible to scale up individual application functions as needed rather than increase total resource allocation for your entire application, which helps reduce total resource costs and improve overall app efficiency. AWS serverless offerings. Enhancing event ingestion.
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