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DevOps and security teams managing today’s multicloud architectures and cloud-native applications are facing an avalanche of data. This has resulted in visibility gaps, siloed data, and negative effects on cross-team collaboration. At the same time, the number of individual observability and security tools has grown.
With our enhanced AWS Lambda extension , we bring the power of Dynatrace PurePath 4 automatic tracing technology to serverless function observability. Serverless can accelerate innovation (and introduce blind spots). However, while they provide significant benefits, serverless functions also pose several challenges.
Key takeaways from this article on modern observability for serverless architecture: As digital transformation accelerates, organizations need to innovate faster and continually deliver value to customers. Companies often turn to serverless architecture to accelerate modernization efforts while simplifying IT management.
The phrase “serverless computing” appears contradictory at first, but for years now, successful companies have understood the benefit of using serverless technologies to streamline operations and reduce costs. So what exactly does “serverless” mean, and how can your organization benefit from it?
For AWS Lambda, Dynatrace provides Lambda Layers for adding distributed tracing to your serverless functions and for capturing metrics and logs from Amazon CloudWatch. Managing multiple data sources and integrations to capture all telemetry signals increases the complexity and TCO of your observability pipeline.
This means, you don’t need to change even a single line of code in the serverless functions themselves. Serverless functions extend applications to accelerate speed of innovation. These serverless functions allow developers to focus on their business logic.
Indeed, according to one survey, DevOps practices have led to 60% of developers releasing code twice as quickly. According to a Gartner report, “By 2023, 60% of organizations will use infrastructure automation tools as part of their DevOps toolchains, improving application deployment efficiency by 25%.”. and 2.14.1.
AWS Lambda is a serverless compute service that can run code in response to predetermined events or conditions and automatically manage all the computing resources required for those processes. It also enables DevOps teams to connect to any number of AWS services or run their own functions. What is AWS Lambda? How does AWS Lambda work?
AI data analysis can help development teams release software faster and at higher quality. So how can organizations ensure data quality, reliability, and freshness for AI-driven answers and insights? And how can they take advantage of AI without incurring skyrocketing costs to store, manage, and query data?
When Amazon launched AWS Lambda in 2014, it ushered in a new era of serverless computing. Serverless architecture enables organizations to deliver applications more efficiently without the overhead of on-premises infrastructure, which has revolutionized software development. Its approach to serverless computing has transformed DevOps.
A DevSecOps approach advances the maturity of DevOps practices by incorporating security considerations into every stage of the process, from development to deployment. DevSecOps practices build on DevOps, ensuring that security concerns are top of mind as developers build code. The education of employees about security awareness.
AWS Lambda is one of the most popular serverless compute services in the market. Serverless functions help developers innovate faster, scale easier and reduce operational overhead, removing the burden of managing underlying infrastructure when updating and deploying code. Insights into how serverless functions impact user experience.
Similar to AWS Lambda , Azure Functions is a serverless compute service by Microsoft that can run code in response to predetermined events or conditions (triggers), such as an order arriving on an IoT system, or a specific queue receiving a new message. The observability problem of the serverless approach. Dynatrace news.
In recent years, function-as-a-service (FaaS) platforms such as Google Cloud Functions (GCF) have gained popularity as an easy way to run code in a highly available, fault-tolerant serverless environment. Google Cloud Functions is a serverless compute service for creating and launching microservices. What is Google Cloud Functions?
IT, DevOps, and SRE teams seeking to know the health of their apps and services have always faced obstacles that can drain productivity, stifle collaboration, ratchet up the time to resolution, and limit the effectiveness of their collaboration with other parts of the business. Dynatrace news.
As organizations look to expand DevOps maturity, improve operational efficiency, and increase developer velocity, they are embracing platform engineering as a key driver. The pair showed how to track factors including developer velocity, platform adoption, DevOps research and assessment metrics, security, and operational costs.
What is a Lambda serverless function? Despite being serverless, the function still requires infrastructure on which to run. There is a new Lambda function handler signature that provides a stream object to which your function can write incoming stream data immediately, without waiting for any buffering as before.
IT, DevOps, and SRE teams are racing to keep up with the ever-expanding complexity of modern enterprise cloud ecosystems and the business demands they are designed to support. Dynatrace news. Leaders in tech are calling for radical change. Observability brings multicloud environments to heel. Another challenge is overcoming alert storms.
Artificial intelligence for IT operations, or AIOps, combines big data and machine learning to provide actionable insight for IT teams to shape and automate their operational strategy. DevOps: Applying AIOps to development environments. DevOps can benefit from AIOps with support for more capable build-and-deploy pipelines.
Conventional approaches to application security can’t keep pace with cloud-native environments that rely on agile methodologies, API-driven architectures, microservices, containers, and serverless functions. By identifying degradation in quality and security throughout the lifecycle, remediation actions can be triggered automatically.
Cloud environment toolkits —microservices, Kubernetes, and serverless platforms — enable business agility, but also create complexity for which many security solutions weren’t built for. Additionally, real-time visibility into production vulnerabilities helps to secure sensitive consumer and employee data. DevOps vs. DevSecOps – blog.
Log4Shell required many organizations to take devices and applications offline to prevent malicious attackers from gaining access to IT systems and sensitive data. As a result, organizations need to be vigilant in identifying and addressing vulnerabilities to protect their systems and data.
Data supports this shift from monolithic architecture to microservices approaches. Combined with Agile or DevOps approaches and methodologies, enterprises can accelerate their ability to deliver digital services. Hard on DevOps. Server-side application. This handles HTTP requests and executive domain-specific logic.
Using a microservices approach, DevOps teams split services into functional APIs instead of shipping applications as one collective unit. Easy to leverage API interfaces connect services with core functionality, allowing applications to communicate and share data. Test early and often using multiple methods. Microservices managed.
Using a microservices approach, DevOps teams split services into functional APIs instead of shipping applications as one collective unit. Easy to leverage API interfaces connect services with core functionality, allowing applications to communicate and share data. Test early and often using multiple methods. Microservices managed.
We start with metrics, traces, and logs (that’s table stakes) but also provide context and enrichment through topology, behavior, code, metadata, and network, combined with data from application programming interfaces (API) and OpenTelemetry. DevOps and Cloud Ops Automation. Application Modernization.
A microservices approach enables DevOps teams to develop an application as a suite of small services. One team may build it, but three separate DevOps and IT teams must maintain it. Serverless platforms. It’s easy to see why, with benefits such as better testing, easier deployment, faster performance, and more. Service mesh.
As a result, IT operations, DevOps , and SRE teams are all looking for greater observability into these increasingly diverse and complex computing environments. 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.
A common challenge of DevOps teams is they get overwhelmed with too many alerts from their observability tools. DevOps teams don’t need just more noise—they need smarter alerting that is automatic, accurate, and actionable with precise root cause analysis. data-raw '{. Davis understands what it can “see.”
Data confirms Aggarwal’s conclusions. Further, Forrester predicted that 25% of developers will use serverless technologies and nearly 30% will use containers regularly by the end of 2021. The research estimated a 35% increase in public cloud usage in 2021 alone. Cloud observability is a known problem for IT pros.
Suddenly, not just DevOps, but infrastructure teams, developers, and operations teams are all challenged to understand how performance problems within applications or cloud services may impact the performance of the overall infrastructure. As a developer, you might use Google Cloud Function for serverless components.
Observability gives developers and system operators real-time awareness of a highly distributed system’s current state based on the data it generates. Traces provide performance data about tasks that are performed by invoking a series of services. What is observability? The case for an integrated observability platform.
For the inaugural O’Reilly survey on serverless architecture adoption, we were pleasantly surprised at the high level of response: more than 1,500 respondents from a wide range of locations, companies, and industries participated. The high response rate tells us that serverless is garnering significant mindshare in the community.
Many organizations turn to cloud migration and cloud application modernization to gain the benefits of serverless environments, such as flexibility, scalability, and more cost-effective cloud infrastructure. . According to some data, 93% of technologists find cloud application modernization challenging. What is serverless computing?
Protecting IT infrastructure, applications, and data requires that you understand security weaknesses attackers can exploit. Cloud infrastructure analysis ensures the secure configuration of cloud infrastructure including virtual machines, containers, cloud-hosted databases, and serverless services. Dynatrace news.
Lifting and shifting applications from the data center to the cloud delivers only marginal benefits. It also enables the agile DevOps development techniques that have been adopted by 83% of IT organizations, according to Puppet. Stateful applications — or those that manage and store data directly — create risk and complexity.
I wanted to leverage Dynatrace’s Environment APIs, for example to export timeseries data, get problem stats, or change configuration settings, like enforcing a certain data privacy setting. TenantCache: a cache to store tenant information and API token information and semi-permanent data to avoid unnecessary roundtrips. ?
AWS Lambda is one of the most popular serverless compute services in the market. Serverless functions help developers innovate faster, scale easier and reduce operational overhead, removing the burden of managing underlying infrastructure when updating and deploying code. Insights into how serverless functions impact user experience.
But managing these three data types at a scale becomes unsustainable for even the most experienced teams. Using a data-driven approach to size Azure resources, Dynatrace OneAgent captures host metrics out-of-the-box to assess CPU, memory, and network utilization on a VM host. Performance Efficiency.
A lot happened between January and the first week of March, when we got around to analyzing our survey data. Among non-adopters, culture seems to be the biggest impediment to cloud adoption: just under 5% of non-adopters cited an “organizational preference to keep data on premises” ( Figure 4 ). All told, we received 1,283 responses.
Anyone moving to the cloud knows that it isn’t just a change from running servers in your data center to running them in someone else’s data center. Just displaying a bunch of metrics on dashboards doesn’t help you solve problems – it overwhelms you with alerts and data. Able to provide answers, not just data.
In my role as DevOps and Autonomous Cloud Activist at Dynatrace, I get to talk to a lot of organizations and teams, and advise them on how to speed up delivery while also increasing the delivery in order to minimize the impact on operations. Dynatrace news. SharePoint – part of Office 365 – is a critical business application for them.
APM solutions track key software application performance metrics using monitoring software and telemetry data. Provide visual data for users to better understand the performance metrics. Its Service Map gives you exactly what you need to trace the path of data flow and how inter-connected micro services are. All rights reserved.
Cloud environment toolkits —microservices, Kubernetes, and serverless platforms — deliver business agility, but also create complexity for which many security solutions weren’t designed. Therefore, application vulnerabilities can proliferate quickly and threaten sensitive employee or customer data. What is Log4Shell?
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