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Business processes support virtually all aspects of an organizations operations. Theyre often categorized by their function; core processes directly create customer value, support processes increase departmental efficiency, and management processes drive strategic goals and compliance.
But to be scalable, they also need low-code/no-code solutions that don’t require a lot of spin-up or engineering expertise. With the Dynatrace modern observability platform, teams can now use intuitive, low-code/no-code toolsets and causal AI to extend answer-driven automation for business, development and security workflows.
A production bug is the worst; besides impacting customer experience, you need special access privileges, making the process far more time-consuming. It also makes the process risky as production servers might be more exposed, leading to the need for real-time production data. This cumbersome process should not be the norm.
Code coverage is a software quality metric commonly used during the development process that let’s you determine the degree of code that has been tested (or executed). To achieve optimal code coverage, it is essential that the test implementation (or test suites) tests a majority percent of the implemented code.
What developers want Developers want to own their code in a distributed, ephemeral, cloud, microservices-based environment. This ownership starts with understanding how their code behaves in all environments, resolving issues, and writing and optimizing code in a high-quality, secure, and timely manner.
A business process is a collection of related, usually structured tasks or steps, performed in sequence, that achieve a defined business goal. Tasks may be manual or automatic, and many business processes will include a combination of both. Make better decisions by providing managers with real-time data about the business.
The VS Code extension Dynatrace Apps is here to streamline your development process and simplify app building. Now you can easily query live data directly within VS Code using the Dynatrace Query Language (DQL). Sound familiar? This aids in effectively handling execution, loading, and error states.
Processes are time-intensive. Slow processes introduce risk. Continuous visibility and assessment provide platform engineering, DevSecOps, DevOps, and SRE teams with the ability to track, validate, and remediate potential compliance-relevant findings and create the necessary evidence for the auditing process. Reactivity.
Carefully planning and integrating new processes and tools is critical to ensuring compliance without disrupting daily operations. Visibility of all business processes starting from the back end and ending with customer experience is perhaps the biggest challenge.
With the increasing amount of sensitive information stored and processed, it’s essential to ensure that systems are secure and protected against potential threats. The deep insights into application code provided by OneAgent® help track potentially vulnerable data flow within an application.
One of the more popular use cases is monitoring business processes, the structured steps that produce a product or service designed to fulfill organizational objectives. By treating processes as assets with measurable key performance indicators (KPIs), business process monitoring helps IT and business teams align toward shared business goals.
Future blogs will provide deeper dives into each service, sharing insights and lessons learned from this process. The Netflix video processing pipeline went live with the launch of our streaming service in 2007. The Netflix video processing pipeline went live with the launch of our streaming service in 2007.
Dynatrace Simple Workflows make this process automatic and frictionlessthere is no additional cost for workflows. Why manual alerting falls short As your product and deployments scale horizontally and vertically, the sheer volume of data makes it impossible for teams to catch every error quickly using manual processes.
In today's data-driven world, organizations need efficient and scalable data pipelines to process and analyze large volumes of data. Medallion Architecture provides a framework for organizing data processing workflows into different zones, enabling optimized batch and stream processing.
Most of these leverage the unique capability of Dynatrace OneAgent® to extract business data from in-flight application payloads — without writing any code. Dynatrace OpenPipeline is a new stream processing technology that ingests and contextualizes data from any source. Business process monitoring and optimization.
Developers are increasingly responsible for ensuring the quality and security of code throughout the software lifecycle. Developer-first observability Adding Rookout to the Dynatrace platform will provide developers with increased code-level observability of Kubernetes-hosted production environments.
by Jun He , Yingyi Zhang , and Pawan Dixit Incremental processing is an approach to process new or changed data in workflows. The key advantage is that it only incrementally processes data that are newly added or updated to a dataset, instead of re-processing the complete dataset.
This link allows us to open Live Debugger and dive into the code level of the AdService (example service) without requiring code changes or application redeployments. We use the automatically populated filter for AdService and its corresponding source code repository, then select Done to go to Live Debugger.
Hence, having a dedicated dashboard tile visualizing the key parameters of each SLO simplifies the process of evaluating them. To implement SLOs in your software delivery cycle and consistently add observability measures from the beginning, Dynatrace “configuration as code” (Monaco and Dynatrace Terraform) will soon support the new API.
Broken Apache Struts 2: Technical Deep Dive into CVE-2024-53677The vulnerability allows attackers to manipulate file upload parameters, possibly leading to remote code execution. This blog post dissects the vulnerability, explains how Struts processes file uploads, details the exploit mechanics, and outlines mitigation strategies.
Organizations choose data-driven approaches to maximize the value of their data, achieve better business outcomes, and realize cost savings by improving their products, services, and processes. Data is then dynamically routed into pipelines for further processing. Commitment to privacy.
Smartscape topology visualizes the relationships between applications, services, processes, hosts, and data centers, highlighting problems and vulnerabilities. Leveraging code-level insights and transaction analysis, Dynatrace Runtime Application Protection automatically detects attacks on applications in your environment.
Introducing sufficient jitter to the flush process can further reduce contention. By creating multiple topic partitions and hashing the counter key to a specific partition, we ensure that the same set of counters are processed by the same set of consumers. This process can also be used to track the provenance of increments.
To pinpoint the exact requests that are failing, the e-commerce team filters by excluding successful HTTP 200 status codes. The team filters further by the “/cart/checkout endpoint” attribute value. This refinement reveals that only a few requests are failing. The team can now dive deeper to find out why.
Findings from various stages of the Software Development Lifecycle (SDLC) are mixed in: code scans, build scans, and runtime. Workflows serves as the automation engine to efficiently process and triage the security findings, create working tickets for your DevSecOps teams, and send notifications to the relevant stakeholders.
Moreover, the OpenTelemetry Collector can measure service span durations, categorized by span names, span kinds, and status codes. This self-monitoring aspect is crucial for maintaining the health and efficiency of the Collector itself, ensuring that it can handle the demands of large-scale data collection and processing without degradation.
After optimizing containerized applications processing petabytes of data in fintech environments, I've learned that Docker performance isn't just about speed it's about reliability, resource efficiency, and cost optimization. We can fix that with this code below: Let's dive into strategies that actually work in production.
These vulnerabilities, identified as CVE-2025-1097 , CVE-2025-1098 , CVE-2025-24514 , and CVE-2025-1974 , allow unauthenticated remote code execution (RCE) and unauthorized access to secrets stored across all namespaces in a Kubernetes cluster. How does an exploit of the IngressNightmare vulnerabilities work?
Metric definitions are often scattered across various databases, documentation sites, and code repositories, making it difficult for analysts and data scientists to find reliable information quickly. DJ then can perform the joins to bring in any requested dimensions from `users_dimension_table`.
This vulnerability, published as CVE-2024-53677 on December 11, 2024, affects the file upload mechanism, allowing for path traversal and potential remote code execution. This critical flaw allows for a path traversal attack, enabling attackers to upload malicious files and potentially execute arbitrary code on the server.
Indeed, according to one survey, DevOps practices have led to 60% of developers releasing code twice as quickly. But increased speed creates a tradeoff: According to another study, nearly half of organizations consciously deploy vulnerable code because of time pressure. Increased adoption of Infrastructure as code (IaC).
This combination allows a malicious actor with local administrative privileges on a virtual machine to execute code as the virtual machine’s VMX process running on the host. It allows a malicious actor with privileges within the VMX process to trigger an arbitrary kernel write, which can lead to an escape from the sandbox.
At the same time, Snyk focuses on various artifacts, conducting comprehensive assessments of code and container repositories. During the SDLC development phases, various artifacts of your applications are assessed for security issues from their code phase throughout the build and deploy phases until they run in your production.
The green frames are the actual instructions running on the AI or GPU accelerator, aqua shows the source code for these functions, and red (C), yellow (C++), and orange (kernel) show the CPU code paths that initiated these AI/GPU programs. The gray "-" frames just help highlight the boundary between CPU and AI/GPU code.
One of the main reasons this feature exists is just like with food samples, to give you “a taste” of the production quality ETL code that you could encounter inside the Netflix data ecosystem. " , country_code STRING COMMENT "Country code of the playback session." This is one way to build trust with our internal user base.
Today, development teams suffer from a lack of automation for time-consuming tasks, the absence of standardization due to an overabundance of tool options, and insufficiently mature DevSecOps processes. This process begins when the developer merges a code change and ends when it is running in a production environment.
It’s also critical to have a strategy in place to address these outages, including both documented remediation processes and an observability platform to help you proactively identify and resolve issues to minimize customer and business impact. Software bugs Software bugs and bad code releases are common culprits behind tech outages.
A natural solution is to make flows configurable using configuration files, so variants can be defined without changing the code. Unlike parameters, configs can be used more widely in your flow code, particularly, they can be used in step or flow level decorators as well as to set defaults for parameters.
Modern observability and security require comprehensive access to your hosts, processes, services, and applications to monitor system performance, conduct live debugging, and ensure application security protection. It automatically discovers and monitors each host’s applications, services, processes, and infrastructure components.
” Junior developers are trained to think that if the code solves the problem, the job is finished. We no longer need to spend loads of time training developers; we can train them to be “prompt engineers” (which makes me think of developers who arrive on time), and they will ask the AI for the code, and it will deliver.
By automating the integration, testing , and deployment processes, CI/CD helps maintain code quality, reduce manual effort, and provide continuous feedback, ultimately leading to faster and more reliable software delivery. CI/CD is important for the following reasons:
With the significant growth of container management software and services, enterprises need to find ways to simplify the process. CaaS automates the processes of hosting, deploying, and managing container technologies. The emergence of Docker and other container services enabled companies to transport code quickly and easily.
Dynatrace Configuration as Code enables complete automation of the Dynatrace platform’s configuration, ensuring that software is secure and reliable. With Configuration as Code, developers can manage their observability and security tasks with config files that can be developed alongside source code conveniently and at scale.
As enterprises expand their software development practices and scale their DevOps pipelines, effective management of continuous integration (CI) and continuous deployment (CD) processes becomes increasingly important. It is critical for managing code repositories, automating tasks, and enabling collaboration among development teams.
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