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Using AWS to Effectively Implement AIOps

Aug 16, 2021
  • aiops digital transformation solutions
  • best ai auto discovery tools
  • Best AIOps Platforms Software
  • digital transformation services and solutions
  • IT Automation with AI
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In this blog post

  • Gain visibility into the Amazon S3
  • Curbs the need for manual scaling
  • Anomaly detection via Amazon CloudWatch
  • Root cause analysis
  • Intelligent threat detection
  • In a nutshell

The rise of AIOps based analytics platforms has helped organizations induce automation in the business processes. AI data analytics monitoring tools rely heavily on huge chunks of data produced by machines to derive insights. Amazon is one of the leading firms in providing components of IT infrastructure to organizations across the world. It has offered various AWS tools that are specifically designed for implementing an AIOps strategy. Find out why AWS is the right tool for effectively implementing AIOps.

Gain visibility into the Amazon S3

Organizations use Amazon S3 for object storage and require high observability to detect data types. Amazon S3 can store numerous types of objects and, it gets difficult to detect sensitive data types from the large pool of data. To tackle this challenge, AWS launched Amazon Macie to discover sensitive data stored in S3. Let’s delve deeper into how Amazon Macie enhances observability into S3:

  • Just like AIOps, Amazon Macie uses pattern matching and AI/ML algorithms to detect sensitive data types.
  • It also uses PII (Personally Identifiable Information) like name, address, and others to automatically detect sensitive data types.
  • Besides discovering standard data types, Amazon Macie can also discover customized data types. You can use regular expressions to discover sensitive data types easily with Amazon Macie.
  • The best AIOps tools and products can be used together with Amazon Macie to increase visibility into the security and privacy of sensitive data. AIOps tools are highly compatible with Amazon Macie to aid organizations in detecting sensitive data types.

Curbs the need for manual scaling

Many organizations use Amazon EC2 for boosting their cloud computing infrastructure. The EC2 fleet size is to be minimized and expanded according to utilization. AIOps-based real-time user monitoring tools can also compute the exhaustive capacity of EC2 instances. However, Amazon offers predictive scaling that completely exempts CXOs from manual intervention. If the workload on your EC2 instances experiences sudden spikes, predictive scaling is the perfect solution for you.

Predictive scaling is a type of AI DevOps platform management service that predicts the spike in the workload of EC2 instances. Based on weekly/daily traffic on EC2 instances, predictive scaling can determine future traffic spikes. You can use AIOps-based predictive analytics models to determine the future performance of software systems. However, with EC2 predictive scaling, you can know the future traffic patterns which, are the main reasons for scaling the computing capacity of your software systems.

Anomaly detection via Amazon CloudWatch

Amazon CloudWatch is among the best AWS cloud monitoring tools. CloudWatch was launched in 2009 but didn’t have anomaly detection as a built-in specification. With the rise of AIOps-based application performance monitoring systems, Amazon offered an anomaly detection feature for CloudWatch in 2019. Amazon CloudWatch can help with anomaly detection in the following ways:

  • CloudWatch’s anomaly detection feature uses ML algorithms. It has its roots in Amazons’ many internal/statistical models signifying its vast capabilities to detect an anomaly.
  • Various metrics are used to measure the application performance monitoring. CloudWatch analyzes the historical data related to performance metrics and finds patterns between the anomalies.
  • Based on the historical data, CloudWatch forms a prediction model that depicts future anomalies. IT professionals that are involved in enhancing service availability will be benefited from Amazon CloudWatch. CloudWatch will provide you with actionable insights which, is also the main function of AIOps-based platforms.
  • You can set CloudWatch alarms that automatically go off once an anomaly is detected. It is among the widely used AI data analytics monitoring tools that collect performance data in form of metrics, logs, and events. You can automate actions for resolving anomalies by using CloudWatch to implement AIOps.

Root cause analysis

Are you unable to find the root cause of security breaches in your IT infrastructure? Amazon Detective is an AI automated root cause analysis solution that helps during security breaches or suspicious behavior. It uses statistical analysis via AI/ML algorithms to find the root cause of a security issue. Unable to find the root cause of a security issue will hamper your service availability. Implementing AIOps security with Amazon Detective will help you in collecting log data from various software systems. The log data collected by Amazon Detective is then organized into a graph model.

The data in the graph model organized by Amazon Detective is continuously updated and, it keeps log data up to a year. It makes tracing security issues and their root cause easier for system administrators. By looking at the aggregated log data, you can easily find the patterns between security issues. Combining log data from various data sources manually is a tricky job as security investigations tend to get lengthy. An AI automated root cause analysis solution can help in conducting faster security investigations.

Intelligent threat detection

Security threats are getting more complex and, businesses are adopting intelligent threat detection to encounter them. Thanks to AIOps, cybersecurity and compliance services can be conducted more effectively. Amazon GuardDuty is another widely used AWS tool for intelligent threat detection. How you can use Amazon GuardDuty to implement AIOps for your organization are as follows:

  • In the backdrop of Amazon GuardDuty are sophisticated AI/ML algorithms that continuously monitor AWS resources. Besides monitoring the data stored in Amazon S3, GuardDuty also monitors AWS accounts and workloads related to your S3 instances.
  • GuardDuty is among the best AIOps solutions in USA that does not require any external software/hardware to deploy. You can activate Amazon GuardDuty in simple steps via the AWS Management Console.
  • GuardDuty will help you in identifying the current as well as the future threats within the IT infrastructure. Not only do you automate security & compliance processes but also save funds from being unnecessarily spent.

In a nutshell

More than a million organizations worldwide are already using AWS resources. The AIOps industry is relatively newer but has an impressive compound annual growth rate of 30%. AWS offers AI tools in IT operations management that can implement the right AIOps strategy for your organization. Start using AWS to effectively implement AIOps for your business!

Tags

  • aiops digital transformation solutions
  • best ai auto discovery tools
  • Best AIOps Platforms Software
  • digital transformation services and solutions
  • IT Automation with AI


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