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As an executive, I am always seeking simplicity and efficiency to make sure the architecture of the business is as streamlined as possible. Generative AI enhances response speed and clarity, accelerating incident resolution and boosting team productivity. Traditional network-based security approaches are evolving.
.” While this methodology extends to every layer of the IT stack, infrastructure as code (IAC) is the most prominent example. Here, we’ll tackle the basics, benefits, and best practices of IAC, as well as choosing infrastructure-as-code tools for your organization. What is infrastructure as code? Consistency.
Infrastructure monitoring is the process of collecting critical data about your IT environment, including information about availability, performance and resource efficiency. Many organizations respond by adding a proliferation of infrastructure monitoring tools, which in many cases, just adds to the noise. Dynatrace news.
More technology, more complexity The benefits of cloud-native architecture for IT systems come with the complexity of maintaining real-time visibility into security compliance and risk posture. Configuration and Compliance , adding the configuration layer security to both applications and infrastructure and connecting it to compliance.
As a result, organizations are weighing microservices vs. monolithic architecture to improve software delivery speed and quality. Traditional monolithic architectures are built around the concept of large applications that are self-contained, independent, and incorporate myriad capabilities. What is monolithic architecture?
This article outlines the key differences in architecture, performance, and use cases to help determine the best fit for your workload. RabbitMQ follows a message broker model with advanced routing, while Kafkas event streaming architecture uses partitioned logs for distributed processing. What is RabbitMQ? What is Apache Kafka?
For organizations running their own on-premises infrastructure, these costs can be prohibitive. Cloud service providers, such as Amazon Web Services (AWS) , can offer infrastructure with five-nines availability by deploying in multiple availability zones and replicating data between regions. What is always-on infrastructure?
Without observability, the benefits of ARM are lost Over the last decade and a half, a new wave of computer architecture has overtaken the world. ARM architecture, based on a processor type optimized for cloud and hyperscale computing, has become the most prevalent on the planet, with billions of ARM devices currently in use.
To address this, state and local governments are adopting multicloud environments to achieve the necessary speed, scale, and agility to keep up with faster digital transformation. The importance of critical infrastructure and services While digital government is necessary, protecting critical infrastructure and services is equally important.
In order for software development teams to balance speed with quality during the software development cycle (SDLC), development, security, and operations teams (or DevSecOps teams) need to ensure that their practices align with modern cloud environments. That can be difficult when the business climate can prioritize speed.
To get a better understanding of AWS serverless, we’ll first explore the basics of serverless architectures, review AWS serverless offerings, and explore common use cases. Serverless architecture: A primer. Serverless architecture shifts application hosting functions away from local servers onto those managed by providers.
To take full advantage of the scalability, flexibility, and resilience of cloud platforms, organizations need to build or rearchitect applications around a cloud-native architecture. So, what is cloud-native architecture, exactly? What is cloud-native architecture? Immutable infrastructure. Stateless whenever possible.
Effective application development requires speed and specificity. This enables teams to quickly develop and test key functions without the headaches typically associated with in-house infrastructure management. FaaS vs. monolithic architectures. Infrastructure as a service (IaaS) handles compute, storage, and network resources.
These include traditional on-premises network devices and servers for infrastructure applications like databases, websites, or email. Without seeing syslog data in the context of your infrastructure, metrics, and transaction traces, you’re slowed down by manual work with siloed data.
Central engineering teams enable this operational model by reducing the cognitive burden on innovation teams through solutions related to securing, scaling and strengthening (resilience) the infrastructure. All these micro-services are currently operated in AWS cloud infrastructure.
Grail architectural basics. The aforementioned principles have, of course, a major impact on the overall architecture. A data lakehouse addresses these limitations and introduces an entirely new architectural design. It’s based on cloud-native architecture and built for the cloud. But what does that mean?
While data lakes and data warehousing architectures are commonly used modes for storing and analyzing data, a data lakehouse is an efficient third way to store and analyze data that unifies the two architectures while preserving the benefits of both. This is simply not possible with conventional architectures. Data management.
But it’s not easy: to pull this off, VFX studios need to build and operate serious technical infrastructure (compute, storage, networking, and software licensing), otherwise known as a “ render farm.” Every VFX studio has a slightly different architecture and workflow, and a one-size-fits-all solution often isn’t enough to bridge the gap.
For IT infrastructure managers and site reliability engineers, or SREs , logs provide a treasure trove of data. These traditional approaches to log monitoring and log analytics thwart IT teams’ goal to address infrastructure performance problems, security threats, and user experience issues. where an error occurred at the code level.
Organizations are accelerating movement to the cloud, resulting in complex combinations of hybrid, multicloud [architecture],” said Rick McConnell, Dynatrace chief executive officer at the annual Perform conference in Las Vegas this week. The demands of digital transformation can create a difficult tightrope for organizations to walk.
Organizations continue to turn to multicloud architecture to deliver better, more secure software faster. To combat the cloud management inefficiencies that result, IT pros need technologies that enable them to gain insight into the complexity of these cloud architectures and to make sense of the volumes of data they generate.
The journey toward business observability Traditional IT monitoring that relies on a multitude of tools to collect, index, and correlate logs from IT infrastructure, networks, applications, and security systems is no longer effective at supporting the need of the wider organization for business insights. Operational optimization.
Transform your operations today with the new Problems app and stay ahead in the ever-evolving software and cloud infrastructure landscape. This is why precisely showing the root cause ultimately helps to speed up problem resolution. Instead, you receive an AI-generated summary as an affected deployment architecture diagram.
But its distributed architecture also introduces significant security challenges. Ease of integration: Look for a solution that integrates seamlessly with your CI/CD pipeline, observability and security solutions, and existing cloud infrastructure. In 2024, misconfigured Kubernetes clusters contributed to 45% of security incidents.
In this blog post, we explain what Greenplum is, and break down the Greenplum architecture, advantages, major use cases, and how to get started. It’s architecture was specially designed to manage large-scale data warehouses and business intelligence workloads by giving you the ability to spread your data out across a multitude of servers.
Overcoming the barriers presented by legacy security practices that are typically manually intensive and slow, requires a DevSecOps mindset where security is architected and planned from project conception and automated for speed and scale throughout where possible. Challenge: Monitoring processes for anomalous behavior.
Trace your application Imagine a microservices architecture with hundreds of dependencies. This architecture also means you’re not required to determine your log data use cases beforehand or while analyzing logs within the new logs app. Interact with data intuitively and easily and benefit from immediate, AI-supported insights.
According to the Dynatrace “2022 Global CIO Report,” 79% of large organizations use multicloud infrastructure. Moreover, organizations have to balance maintaining security, retaining cloud management expertise, and managing infrastructure performance. Rural lifestyle retail giant Tractor Supply Co.
The growing challenge in modern IT environments is the exponential increase in log telemetry data, driven by the expansion of cloud-native, geographically distributed, container- and microservice-based architectures. Organizations need a more proactive approach to log management to tame this proliferation of cloud data.
Log monitoring, log analysis, and log analytics are more important than ever as organizations adopt more cloud-native technologies, containers, and microservices-based architectures. Log analytics also help identify ways to make infrastructure environments more predictable, efficient, and resilient. Dynatrace news. What are logs?
IT pros need a data and analytics platform that doesn’t require sacrifices among speed, scale, and cost. Therefore, many organizations turn to a data lakehouse, which combines the flexibility and cost-efficiency of a data lake with the contextual and high-speed querying capabilities of a data warehouse. Learn more.
Dynatrace supports full-stack monitoring for Kubernetes, from the application down to the infrastructure layer. However, if you don’t have access to the infrastructure layer, Dynatrace also provides the option of application-only monitoring. Can mount a volume to speed up injection for subsequent pods.
Complexity and data volume for IT infrastructure soars to new heights. The volume of data and events grows in tandem with the rising complexity of IT infrastructure. Monitoring modern IT infrastructure is difficult, sometimes impossible, without advanced network monitoring tools.
Deploy risk-based estimates and models with confidence, accuracy, transparency, and speed. Optimize the IT infrastructure supporting risk management processes and controls for maximum performance and resilience. The IT infrastructure, services, and applications that enable processes for risk management must perform optimally.
Platform engineering creates and manages a shared infrastructure and set of tools, such as internal developer platforms (IDPs) , to enable software developers to build, deploy, and operate applications more efficiently. As a result, teams can focus on writing code and building features rather than dealing with infrastructure nuances.
Site reliability engineering (SRE) is the practice of applying software engineering principles to operations and infrastructure processes to help organizations create highly reliable and scalable software systems. Dynatrace news. What is site reliability engineering? SRE drives a “shift left” mindset. Solving for SR.
However, cloud infrastructure has become increasingly complex. Further, the delivery infrastructure that makes this happen has also become complex. IT pros want a data and analytics solution that doesn’t require tradeoffs between speed, scale, and cost. Much of the software developed today is cloud native.
Its ability to densely schedule containers into the underlying machines translates to low infrastructure costs. The following figure shows the high-level architecture where any load testing solution (e.g. That is because Kubernetes provides several benefits from a performance perspective.
DevSecOps and ITOps teams can then perform tasks with accuracy at the speed a business requires. The core benefits of an AIOps-automated software analytics platform include the following: Infrastructure monitoring. For more information, read our guide on how data lakehouse architectures store data insights in context.
This enables us to optimize their experience at speed. Our A/B tests range across UI, algorithms, messaging, marketing, operations, and infrastructure changes. Instead of relying on engineers to productionize scientific contributions, we’ve made a strategic bet to build an architecture that enables data scientists to easily contribute.
The SSO service disruption occurred due to a new implementation of one of the Account Management screens’ inefficient use of the SSO API, which caused an excessive load to the underlying SSO infrastructure.
Infrastructure Optimization: 100% improvement in Database Connectivity. Reducing performance and architectural issues in their backend system gave them a 99% performance improvement! A highly distributed architecture like this has a lot of potential for performance and architectural hotspots.
As teams try to gain insight into this data deluge, they have to balance the need for speed, data fidelity, and scale with capacity constraints and cost. In most cases, especially with more complex queries, Grail gives you answers at five to 100 times more speed than any other database you can use right now.”
Cloud application security remains challenging because organizations lack end-to-end visibility into cloud architecture. As organizations migrate applications to the cloud, they must balance the agility that microservices architecture brings with the complexity and lack of transparency that can also come with it.
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