To integrate Amazon Firehose and Logentries with your monitoring system, please reach out to MetricFire. Book a demo with the MetricFire team to discuss integrating Amazon Firehose and Logentries and how that can support your monitoring system.
With the ever-increasing popularity of streaming content, the need to enable users to collect, store, capture, and process large amounts of data from their distributed streams is crucial. By using Amazon Kinesis Data Firehose, you can capture massive amounts of live video data from millions of sources, and then make them available to consumers in a data-efficient and cost-effective format.
Amazon Kinesis Data Firehose lets you quickly load streaming data into data stores, data lakes, and analytics services. You can use it to capture, transform, and deliver streaming data to a range of Amazon services, including Amazon Redshift, Amazon S3, Amazon Elasticsearch Service. You can also use Kinesis to connect to generic HTTP endpoints and service providers such as New Relic, MongoDB, Datadog, and Splunk.
Firehose is a fully managed service that automatically scales to match your data throughput. You can also use it to compress, transform, and encrypt your data streams. This feature minimizes the amount of storage required for your streaming data and increases security.
Amazon Kinesis Data Firehose integrates with Amazon CloudWatch metrics so you can collect and analyze your data streaming metrics. For example, you could monitor the IncomingBytes and IncomingRecords metrics to track data ingested into Kinesis Data Firehose from your data producers. You can use Kinesis Analytics to analyze and process your data streams using standard SQL. It also comes with pre-built stream processing templates to help you manage your data analytics.
By integrating Amazon CloudWatch with the MetricFire platform, you can display your streaming metrics on aesthetically pleasing dashboards. MetricFire's advanced filtering lets you choose only the data views you want to see and discard the rest. You can also set up simple rules to discard data you no longer need, plus receive alerts via email or Slack when your data streaming is doing something it shouldn't.
Logentries is a service that automatically collects and centralizes all of your log data into one secure location in any format. From there, you can search and visualize all your aggregated log data. It uses both agent-based and agentless collection of logs. If an issue occurs, Logentries shows an aggregated tail view so you can review what is happening across your logs in real-time. With Logentries, you can dramatically reduce the time you spend diagnosing and resolving issues.
Logentries is a fully scalable service that dynamically auto-scales your services environment as log volumes expand and change. By aggregating all your logs into one secure location, you can efficiently monitor and track valuable log events in real-time, without the hassle of complicated configurations.
Logentries lets you monitor and track essential server resource usages, such as CPU, memory, and network and disk usage. Plus, it aggregates all server and application logs. By aggregating all your logs in one place, you can quickly review your application performance metrics, usage trends, and application load. This strategy helps you better understand how end-users are using your applications and how their behavior might affect other performance metrics.
You can use your log data to better understand application activity from client-side front-end apps to your back-end components for fine-grained user tracking. And while Logentries offers a straightforward, real-time approach to monitoring and accessing valuable application usage data, there is an even better way to monitor your aggregated log data.
By integrating Logentries with the Metricfire platform, you can turbocharge your log monitoring services to new levels and enjoy metrics displayed on aesthetically pleasing dashboards. You can import Logentries data into Hosted Graphite using the leexportpy tool. This flexible and extensible Python application enables log search results to be easily exported to third-party services, including MetricFire.
To integrate Amazon Firehose and Logentries with your monitoring system, sign up for a free trial with MetricFire. Talk with the MetricFire team about how to integrate Amazon Firehose and Logentries and get Amazon Firehose and Logentries interacting with your MetricFire dashboards directly.
MetricFire is a full-scale platform that provides infrastructure, system, and application monitoring using a suite of open-source monitoring tools. We enable you to use Hosted Graphite and aesthetic custom dashboards to visualize your metrics so you can understand what is happening.
MetricFire offers users a complete ecosystem of end-to-end infrastructure monitoring, comprised of popular open-source monitoring software services: Graphite and popular dashboards. Plugins for many other open-source projects are preconfigured, such as StatsD, collectd, and Kubernetes. You get all these within a hosted environment as a single product. Not only does MetricFire fit well into the infrastructure monitoring use-case, such as network monitoring and server monitoring, but we also do application monitoring and business intelligence.
Through this hosted environment, MetricFire boosts the unique features of open-source projects to give you more functionality than the original products. Below are some of the MetricFire features at a glance:
The key thing to remember is that Hosted Graphite by MetricFire is more than just Graphite. Our Hosted Graphite product actually adds data dimensionality and better data storage.
The benefits of MetricFire are:
Why thousands of engineers choose us:
Vendor lock-in's not our thing. We’re believers in you still owning your data, so you can request a full export at any time. That means you get all the benefits of an open-source tool, but with the security and stability of a SaaS tool.
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Transparency is at the root of how we operate: from pricing to postmortems we're open about how we do things. We even publish our internal system metrics to our public status page.
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