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x runtime versions of Azure Functions running in an Azure App Service plan. This gives you deep visibility into your code running in Azure Functions, and, as a result, an understanding of its impact on overall application performance and user experience. Azure Functions in a nutshell. Simplify error analytics.
What is Azure Functions? 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 growth of Azure cloud computing.
By contextualizing data, OpenPipeline enhances the Dynatrace platform’s ability to offer AI-driven insights, analytics, and automation across observability, security, software lifecycle, and business domains. Seamless integration with AWS Data Firehose: address high-impact issues quickly through real-time, high-frequency log analytics.
PurePath 4 supports serverless computing out-of-the-box, including Kubernetes services from Amazon Web Services (AWS) , Microsoft Azure , and Google Cloud Platform (GCP). FaaS like AWS Lambda and Azure Functions are seamlessly integrated with no code changes. Waterfall visualization of all requests.
x runtime versions of Azure Functions running in an Azure App Service plan. This gives you deep visibility into your code running in Azure Functions, and, as a result, an understanding of its impact on overall application performance and user experience. Azure Functions in a nutshell. Simplify error analytics.
These functions are executed by a serverless platform or provider (such as AWS Lambda, Azure Functions or Google Cloud Functions) that manages the underlying infrastructure, scaling and billing. Data analysis : how to process, aggregate and query observability data from serverless functions effectively, accurately, and comprehensively?
To reduce the manual effort of account reconciliation and running the scripts, they converted the Python scripts to Lambda functions. This gave them a separate Lambda function for every Dynatrace environment in their managed cluster. “We were early adopters of OneAgent Lambda monitoring.
We added monitoring and analytics for log streams from Kubernetes and multicloud platforms like AWS, GCP, and Azure, as well as the most widely used open-source log data frameworks. After a function is executed, Lambda logs both the actual duration of the function and the billed duration of the function.
New analytics view for message queues. Fixed an issue in which the Client IP of an AWS Lambda invoked via API Gateway and monitored with OneAgent for AWS Lambda (Python, Node, Java) was additionally redundantly displayed as proxy IP. (APM-325810). Dynatrace API. In the Dynatrace menu , go to Queues. APM-325810). APM-333310).
When Amazon launched AWS Lambda in 2014, it ushered in a new era of serverless computing. Common use-cases for AWS Lambda in the enterprise (and how to get observability for them. What are the typical use cases for AWS Lambda? What are the challenges related to operating Lambda functions? What is AWS Lambda?
Azure supporting services (Synapse Analytics). Lambdas, EBS, and supporting services on the AWS details page are correctly displayed when a management zone filter is selected with the management zone not containing the whole AWS account. Otherwise, Session Replay will stop working once Dynatrace SaaS version 1.238 is live.
Challenges of adopting OpenTelemetry The first challenge is that OpenTelemetry only gathers and processes data—it has no back end, no storage, and no analytics. Using Dynatrace OneAgent adds automatic data collection and enables user behavior analytics and application security use cases, as well as code-level analytics and profiling.
Cluster and container Log Analytics. With the existing notification integrations for tools such as Slack, xMatters, ServiceNow, Lambda, JIRA, you can also pro-actively notify people in case there’s a problem: Dynatrace auto detected a problem with 3 kube proxies. 3 Log Analytics. Full-stack observability. Service mash insights.
Gandalf: an intelligent, end-to-end analytics service for safe deployment in cloud-scale infrastructure , Li et al., This paper describes Gandalf, the software deployment monitor in production at Microsoft Azure for the past eighteen months plus. In Azure, most catastrophic issues happen within 1 hour after the rollout.
When analyzing telemetry from a large population of data sources, such as a fleet of rental cars or IoT devices in “smart cities” deployments, it’s difficult if not impossible for conventional streaming analytics platforms to track the behavior of each individual data source and derive actionable information in real time. The list goes on.
When analyzing telemetry from a large population of data sources, such as a fleet of rental cars or IoT devices in “smart cities” deployments, it’s difficult if not impossible for conventional streaming analytics platforms to track the behavior of each individual data source and derive actionable information in real time. The list goes on.
AWS is far and away the cloud leader, followed by Azure (at more than half of share) and Google Cloud. But most Azure and GCP users also use AWS; the reverse isn’t necessarily true. However, close to half (~48%) use Microsoft Azure, and close to one-third (~32%) use Google Cloud Platform (GCP). Serverless Stagnant.
Most of the CMS vendors dodge questions of evolution by talking about incremental innovation primarily focused on customer experience (CX) such as analytics and personalisation. Alternatively, you can upload output directory to cloud object/blob storage such as Amazon S3 or Azure Blob Storage and serve your site from there.
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