Monitoring & Observability
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Monitoring & Observability
Observability and monitoring have become significant terms in the software delivery process, especially when addressing software development. No matter how much effort you put into developing high-quality software applications, there will always be errors and defects, as the number of users grows and the software application becomes more complicated. For all of these reasons, our system should be observable. The software delivery culture is evolving and trending away from it.
Although both on-premises and cloud-native apps are supposed to be highly available and resilient to failure, the methods utilized to achieve those goals differ. Monitoring has several advantages, including increased productivity and efficiency, the ability to properly allocate resources based on user needs, and the ability to discover and rectify problems before they damage your organization. As a result, you can better allocate your time and move on to new initiatives.
Monitoring
Monitoring is a tool or a technical solution that enables teams to see and comprehend the state of their systems. Monitoring is accomplished by collecting preset sets of metrics or logs.
Observability is a set of tools or technical solutions that enables teams to actively debug their systems. Observability is based on the exploration of unknown qualities and patterns.
Observability
Our team has the following skills to perform well in monitoring and observability:
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Reporting on overall system health (Are my systems operational? Are my systems equipped with enough resources?).
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Reporting on the state of the system as seen by customers (Do my customers know if my system is down and they have a negative experience?).
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Monitoring for critical business and systems metrics.
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Tooling to assist you in understanding and debugging your production systems.
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Using a tool to learn about subjects you didn't know before (that is, you can identify unknown areas).
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Access tools and data that help trace, understand, and diagnose infrastructure problems in your production environment, including service interactions.
Provided Alerting Solutions
Prometheus
Prometheus is an open source monitoring and alerting toolset for containerized services and applications. The project began at SoundCloud and later became a part of the Cloud Native Computing Foundation (CNCF). Prometheus is becoming the industry standard for containerized infrastructure as well as traditional implementation scenarios, particularly in Kubernetes clusters. To enable faultless and safe digital interactions, combine the power of Prometheus with Ecogreensoft's cognitive analytics, scalability, and automation.
Features
Prometheus provides ultimate features and there are many different features as mentioned below:
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A multidimensional data model containing time series data denoted by metric name and key/value pairs.
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PromQL is a versatile query language that takes advantage of this dimensionality.
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There is no reliance on distributed storage; single server nodes are autonomous.
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The time data are collected using a pull approach over HTTP.
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An intermediary gateway is used to push time series.
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Service discovery or static configuration is used to find targets.
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Support for numerous graphing and dashboarding modes.
Components
The Prometheus ecosystem consists of multiple components, many of which are optional:
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The primary Prometheus server for scraping and storing time series data.
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Client libraries for instrumenting application code.
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A push gateway for supporting temporary jobs.
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Exporters for services like as HAProxy, StatsD, Graphite, and others.
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An alertmanager to deal with alerts.
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Numerous assistance tools.
When does it fit?
Prometheus is an excellent tool for recording solely numerical time series. It is appropriate for both machine-centric monitoring and monitoring of highly dynamic service-oriented architectures. Its support for multi-dimensional data collecting and querying is a particular asset in a world of microservices.
Prometheus is built for dependability, to be the system you turn to during an outage to swiftly diagnose problems. Each Prometheus server is self-contained and does not rely on network storage or other distant services. It can be relied on when other portions of your system fail, and it does not require considerable infrastructure to use.
When does it not fit?
Prometheus appreciates dependability. Even when your system is down, you may always see what statistics are accessible about it. If you require 100% accuracy, such as for per-request payment, Prometheus is not a good alternative because the collected data will most likely be insufficiently precise and complete. In this instance, you should use another system to gather and analyse data for billing, and Prometheus for the rest of your monitoring.
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Grafana
Grafana is an open source analytics and interactive visualization web application that runs on multiple platforms. When connected to supported data sources, it generates charts, graphs, and alerts for the web. Grafana Enterprise, a licensed version with enhanced functionality, is now available as a self-hosted installation or as an account on the Grafana Labs cloud service. It can be expanded via a plug-in system. Using interactive query builders, end users may develop complicated monitoring dashboards. Grafana is separated into two parts: the front end and the back end, which are written in TypeScript and Go, respectively. Grafana allows users to visualize their data by combining charts and graphs into a single dashboard (or numerous dashboards) for easier interpretation and comprehension. You may also query and set alerts on your data and metrics from wherever it is kept, whether it is in traditional server environments, Kubernetes clusters, or multiple cloud services, etc.
Key Features
Features provided by Grafana:
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Panels: use histograms, graphs, geo-maps, heatmaps, and other tools to visualize your data in any way you choose.
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Plugins: Using panel plugins that tie into current data sources, you may render your data in real time on a user-friendly API—no data migration required. You may also build data source plugins that pull metrics from any custom API.
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Alerts: You can generate, aggregate, and control all of your alerts from a single user interface.
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Transformations: Rename, summarize, combine, and perform calculations across data sources and queries.
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Annotations: Use rich events from different data sources to annotate graphs.
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Panel Editor: A consistent user interface for configuring and customizing your panels.
Facilities offered by Grafana
Let’s go through the features offered by the open-source analytics dashboard framework:
This open-source framework takes care of all the analytics of our app. We can easily query, visualize, set up alerts, understand the data with the help of metrics.
The dashboard is pretty equipped, & continually evolving, to make sense of complex data. From displaying graphs to heatmaps, histograms, and Geo maps. The tool has a plethora of visualization options to understand data as per our business requirements.
Alerts are set up & triggered like tripwires whenever an anticipated scenario occurs. These happenings can be notified on Slack or whatever communication platform the monitoring team uses.
Grafana has native support for approx. a dozen databases. And with many more, facilitated by respective plugins.
Either host it on-prem or on any cloud platform of your choice.
It has built-in support for Graphite & expressions like add, filter, average , min, max functions etc. to custom fetch data.
It also has a built-in Influx DB, Prometheus, ElasticSearch, and CloudWatch support.
Management levels
As an independent software vendor (ISV), Grafana offers 3 different levels of management to suit the flexible needs of growing businesses.
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Grafana Cloud
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Grafana Enterprise Stack
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Grafana OnCall
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New Relic
New Relic is a software development tool that supports observability. You can bring in data from any digital source so that you can fully understand your system and how to improve it.
Using New Relic you can:
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Bring together all of your data: Using our agents, connectors, and APIs, instrument everything, import data from your whole technology stack, and access it from a single UI.
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Get all of your data at your fingertips and analyze it to identify the sources of issues and improve your processes. Create charts and dashboards using our robust query language.
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Rapid incident response is possible thanks to our machine learning solution, which proactively finds anomalies, explains them, and alerts you before they become a problem.
Solution to all your problems in one place
Rapid issue response is possible thanks to our machine learning technology, which proactively finds anomalies, explains them, and alerts you before they become a problem. No matter where your data comes from, capture, organize and interpret it in New Relic. Utilize Ecogreensoft's agents and integrations to automatically gather information from widely used frameworks and tools, or utilize our APIs for information that is more specialized to your industry or technology.
Analyze your data
Whether it's metrics, events, logs, or traces, Ecogreensoft can help you manage, process, and interpret your data while keeping your data secure at New Relic:
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Visually explore your data: Enter our data explorer to quickly navigate all of your data and connect your entities without needing to know any query languages.
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Utilize our curated dashboard visualizations or make your own to query and visualise your data. To further explore queries and slice and dice your data, use NRQL (New Relic Query Language).
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Query your data programmatically: Access your data through our NerdGraph GraphQL API. Easily prototype queries in our GraphiQL editor.
Respond to incidents faster
To guarantee that their systems are constantly online and operating effectively, DevOps, site-reliability, and network operation teams require trustworthy, real-time alerts and anomaly detection.
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Allow our hybrid machine learning engine for applied intelligence to automatically identify abnormalities, decrease alert noise, and add context to situations so that you can react to them more quickly.
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Proactive detection: Get warned when an app behaves strangely and have an analysis delivered to Slack. Not a Slack user? Create a webhook to automatically deliver messages as needed.
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Receive alerts: Create alerts for all of your data sources so you may be informed when systems require your attention. Maintain your focus and decide how many threshold violations should occur before you are informed.
System context monitoring with New Relic:
New Relic is a Software as a Service offering that focuses on performance and availability monitoring. It uses a standardized Apdex (application performance index) score to set and rate application performance across the environment in a unified manner.
Key features of New Relic include:
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End-to-end user monitoring through browser support.
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External services performance monitoring.
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Availability and error monitoring.
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Key business transaction monitoring.
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Synthetic monitoring.
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Alerts and notifications.
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Native integration with third-party tools such as Slack and PagerDuty.
New Relic supports several application runtimes. This scenario uses a simple microservices-based online store example to demonstrate how to install the New Relic agents and monitor application behaviour.
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Elasticsearch
Built on Apache Lucene, Elasticsearch is a distributed search and analytics engine. Elasticsearch, which was introduced in 2010 and has since grown to be the most widely used search engine, is frequently used for use cases involving log analytics, full-text search, security intelligence, business analytics, and operational intelligence.
Using the Elasticsearch API, you can transmit Elasticsearch data in the form of JSON documents. Elasticsearch automatically adds a searchable reference to the original document and stores it in the cluster's index. The Elasticsearch API can then be used to search for and retrieve the document. Additionally, you can visualise your data and create interactive dashboards using Kibana, a visualisation tool, in conjunction with Elasticsearch.
What is Elasticsearch used for?
Elasticsearch can be used for a variety of use cases due to its speed, scalability, and capacity to index a wide variety of content formats, including the following:
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Application search
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Website search
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Enterprise search
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Logging and log analytics
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Infrastructure metrics and container monitoring
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Application performance monitoring
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Geospatial data analysis and visualization
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Security analytics
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Business analytics
Why use Elasticsearch?
Elasticsearch is by its by nature distributed. Elasticsearch distributes the documents it stores among various shards, or containers, which are copied to give multiple copies of the data in the event of hardware failure. Elasticsearch can grow out to hundreds (or even thousands) of servers and manage petabytes of data thanks to its distributed architecture.
Elasticsearch is fast. Elasticsearch excels at full-text search because it is based on Lucene. Elasticsearch is also a "near real-time" search platform, which means that the time it takes for a document to get from being indexed to being searchable takes only about one second on average. Elasticsearch is hence well suited for time-sensitive use cases like infrastructure monitoring and security analytics.
Elasticsearch comes with a wide set of features. Elasticsearch includes a variety of strong built-in capabilities, such as data rollups and index lifecycle management, that increase the efficiency of storing and searching for data in addition to its speed, scalability, and resilience.
The Elastic Stack simplifies data ingest, visualization, and reporting. It is simple to handle data before indexing it into Elasticsearch thanks to integration with Beats and Logstash. Additionally, Kibana offers UIs for swiftly obtaining data from logs, infrastructure metrics, and application performance monitoring (APM) in addition to real-time viewing of Elasticsearch data.
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Kibana
Kibana is an open-source data visualization and exploration tool for log and time-series analytics, application monitoring, and operational intelligence use cases. Histograms, line graphs, pie charts, heat maps, and integrated geographic capabilities are just a few of the useful and powerful features available. Kibana works in sync with Elasticsearch and Logstash which together forms the so-called ELK stack. ELK stands for Elasticsearch, Logstash, and Kibana. ELK is one of the popular log management platforms used worldwide for log analysis. In the ELK stack, Logstash extracts the logging data or other events from different input sources. It processes the events and later stores them in Elasticsearch.
The log data that is gathered in the "Elasticsearch clusters" can be visualised and explored using Kibana's visual interface software. Elastic is the main company that created Kibana. Elasticsearch and Logstash are two of Kibana's most used tools. These programmes are free to use.
Elasticsearch - This technology will serve as a sizable database for both document-oriented and semi-structured data.
Logstash – This tool helps to store logs, and collect and parse them for future use.
Why use Kibana
Kibana is the best tool for supporting the following because of its close integration with Elasticsearch and the larger Elastic Stack:
Features of Kibana :
There are a lot of Features and benefits of using PagerDuty that can help you with your workload:
Visualization
There are many simple ways to visualize data in Kibana. Examples of some of the ones that are frequently used include heat maps, pie charts, line graphs, vertical bar charts, and horizontal bar charts.
Dashboard
When we have the visualizations ready, all of them can be placed on one board – the Dashboard. Observing different sections together gives you a clear overall idea about what exactly is happening.
Dev Tools
Increase democratic participation in agile response while maintaining continuity with your current procedures.
Gather monitoring data and have complete control over which PagerDuty occurrences are synced with your ticketing software. PagerDuty automates procedures based on best practices, allowing you to concentrate on incident response activities that are more valuable. Teams can manage themselves individually and work freely while maintaining visibility thanks to granular and scalable permissions.
Your organization may do away with information barriers between its people, processes, and data by centralizing information without restricting how employees operate.
Reports
All of the data in the dashboard and visualization formats can be exported as reports (in CSV format), code snippets, or URLs that can be shared with others.
Timelion
Another visualization tool that is generally used for time-based data analysis is Timelion, sometimes known as a timeline.
When working with a timeline, we must employ a straightforward expression language that enables us to connect to the index and do calculations on the data to provide the desired results.
Comparing data to the prior cycle in terms of the week, month, etc. is more helpful.
Advantages of Kibana
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It is a free, open-source browser-based visualization application that is primarily used to analyze massive amounts of log data using heat maps, line graphs, and bar graphs, among other visualizations.
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Simple and easy for beginners to understand.
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Dashboard and visualization conversion into reports is simple.
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Easy analysis of complex data is made possible through the canvas.
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Kibana's Timelion visualisation makes it easier to compare data in reverse to better analyse performance.
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Logging and log analytics.
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Infrastructure metrics and container monitoring.
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Application performance monitoring (APM).
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Geospatial data analysis and visualization.
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Security analytics.
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Business analytics.
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Using a web interface, control, manage, and secure an Elastic Stack instance.
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centralising access for integrated Elastic Stack applications for observability, security, and enterprise search.
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Elasticsearch-indexed data may be found, viewed, and visualized, and the data can be examined by creating bar charts, pie charts, tables, histograms, and maps. These visual components are combined into a dashboard display, which can then be shared via a browser to enable real-time analytical perspectives into massive amounts of data in support of use cases like:
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Nagios
Computer system monitoring software called Nagios is available for free. It was created to function with the Linux operating system and can keep track of computers running that, Windows, and Unix systems (OSes).
The Nagios software performs routine checks on important application, network, and server resource metrics. Nagios, for instance, may track log files, processor load, memory utilisation, disc usage, and microprocessor load. The Simple Mail Transfer Protocol (SMTP), Post Office Protocol 3 (POP3), Hypertext Transfer Protocol (HTTP), and other widely used network protocols are among the services that Nagios can monitor. Passive checks come from external programmes connected to the monitoring tool, whereas active checks are started by Nagios.
Why We Need Nagios tool?
Here are the important reasons to use Nagios monitoring tool:
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Detects all types of network or server issues
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Helps you to find the root cause of the problem which allows you to get the permanent solution to the problem
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Active monitoring of your entire infrastructure and business processes
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Allows you to monitors and troubleshoot server performance issues
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Helps you to plan for infrastructure upgrades before outdated systems create failures
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You can maintain the security and availability of the service
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Automatically fix problems in a panic situation
Features of Nagios
The following are some crucial characteristics of the Nagios monitoring tool:
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Secure, Manageable, and comparatively scalable.
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A reliable database and log system.
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beautiful and educational web interfaces.
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Send notifications automatically if a condition changes.
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It is not necessary to verify that the host is still alive if the services are functioning properly.
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Aids in identifying network issues or server breakdowns.
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The server's performance problems can be fixed.
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If there are any problems, they can be resolved automatically as soon as they are discovered throughout the monitoring process.
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With a single pass, the complete business process and IT infrastructure may be monitored.
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The architecture of the product makes it simple to create new plugins in your preferred language.
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Utilizes topology to determine dependencies.
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Monitor network services like HTTP, SMTP, HTTP, SNMP, FTP, SSH, POP, etc.
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Helps you to define network host hierarchy using parent hosts.
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Ability to define event handlers which runs during service or host events for proactive problem resolution.
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Support for implementing redundant monitoring hosts.
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