The mission-critical problem of too many
Developers and IT engineers might fondly reminiscence the days when learning one tool or application was enough to excel at a task; statements like out of scope or not under core expertise were paid attention to by clients, or the latter were willing to shell out boatloads for every skill upgrade. In the modern world, developers and IT engineers must own projects end-to-end. The underlying language or infra, platforms stack doesn't matter, business operations must run agile whatever the use case is; sudden traffic boosts, expansion into different regions, integration of new-gen technologies, launching innovative new products and services.
believe modern cloud and IT environments are too complex to be manually managed
Around 3 out
of every 5 CIOs
believe they can't complete committed digital projects on time because too much resources are spent to keep the lights on
expect IT headcounts to lag behind the increase in application workloads
Autonomous IT Operations: A Future that Needs to be Accelerated?
Autonomous ITOps is the glittery term expounding a day when IT systems and processes would be fully self-governing, mastering powerful automation, Big Data, and no surprise, AI. That entitles intelligent IT platforms self-monitoring all connected assets (Infra, middle-layers, applications, databases, workloads), self-analyzing the data noise and filtering out actual performance anomalies or predicting possible frictions, self-initiating corrective actions, and self-upgrading resources for modernized outcomes at minimum costs. While that might seem utopia for IT engineers, in reality the latter can then focus on more strategic functions at peace; new solutions and technologies to onboard, expand the existing stack to accommodate new product releases, better end consumer experiences, and drive enterprise-wide digital transformation initiatives at no risk or maintenance hassle!
Here's an example. Let's assume a simple networking fault affecting availability of an application module. The archaic IT management method would be to put the best of network engineers together in a mad scramble, spend hours in finding the root cause, and then expense a few hours more to patch it; result a working day passed in all safe humor. The modern IT managed services philosophy, involving cloud operations, mean such a disruption will be diagnosed by cloud-integrated monitoring tools, ML algorithms co-relate the possible disruption with similar events in its data history and predict a possible root cause of the anomaly which is taken up by a networking professional, at the client or MSP's end as per the SLA. In the Autonomous ITOps utopia, once the fault is detected and diagnosed intelligently, the same shall be automatically patched by the system and the application module is made available, in seconds. In an ideal scenario, the situation might not arise at all because the self-governing system at the autonomous core had analyzed data patterns and predicted a possible outage beforehand, patching it even before it could occur.
Running on AWS? Kickstart on the Autonomous Vision with AI-enabled Managed Services
De-cluttering 24/7 maintenance of multiple, hybrid landscapes could be primary but IS NOT the only reason firms must opt for AI-driven ITOps or AIOps. The business benefits are unparalleled if AI-ML tools are deployed in sync with the core cloud landscape, such as AWS. All public cloud providers, including the former, are investing heavily into AI and promote the usage of intelligent technologies in better governing their cloud stack, maximizing outcomes and ROI, and most importantly run at no risk.
Here's why every business must hunt for an AI-enabled managed services partner or an AIOps-driven MSP if planning their IT transformations on AWS:
- Cost Optimizations: AI and ML can help optimize your AWS infrastructure and applications by identifying cost-saving opportunities. An MSP with AI/ML capabilities can continuously analyze your usage patterns and recommend cost-effective adjustments, such as rightsizing instances or automating resource provisioning.
- Performance Optimizations: AI and ML can also be used to enhance the performance of your AWS workloads. They can monitor your applications, detect anomalies, and make real-time adjustments to improve response times and resource utilization, ensuring a better user experience.
- Security and Compliance Management: AI-powered threat detection and compliance monitoring tools can help protect your AWS environment. An MSP with AI/ML expertise can implement and manage these tools to detect and respond to security threats and maintain regulatory compliance.
- Automation and DevOps: AI and ML can automate various routine tasks, such as scaling resources, managing backups, and optimizing resource allocation. This reduces manual effort, minimizes the risk of errors, and ensures efficient operations. AI-powered DevOps tools help automate and intelligently manage the entire software development lifecycle, accelerating go to market timelines for newer products at next to nil errors.
- Predictive Maintenance: AI/ML can predict potential issues with your AWS infrastructure and applications before they cause downtime. By partnering with an MSP that leverages these technologies, you can proactively address and mitigate problems, improving overall system reliability.
- Scalability: As your AWS environment grows, AI and ML can help ensure that it scales efficiently. An MSP that incorporates these technologies can automatically adjust resources based on workload demand, allowing you to avoid overprovisioning or under-provisioning.
- Data Insights: AI and ML can analyze data generated by your AWS workloads, providing valuable insights for decision-making. MSPs with AI/ML capabilities can help you extract actionable information from your data, leading to better business outcomes.
- Data Storage: AI and ML-powered AWS-native managed storage solutions can transform your data operations from data access management, data availability, insights generation, business intelligence, and data security and backup perspectives. Competent MSPs can charter such data transformations frictionless without any security or compliance risks.
- 24/7 Monitoring and Support: AI/ML-enabled tools can provide around-the-clock monitoring, allowing for quick issue identification and resolution. An MSP can offer continuous support, enhancing the availability and reliability of your AWS services.
- Expertise and Skill Set: Managing AI and ML technologies requires specialized knowledge and skills. By partnering with an MSP that possesses these capabilities, you can leverage their expertise without having to develop in-house AI/ML skills.
- Competitive Advantage: By utilizing AI/ML technologies in your AWS environment, you can gain a business competitive edge. An MSP with these capabilities can help you innovate and stay ahead of industry trends, ensuring quality assessment of innovative technologies and integration of same.
Route to Intelligent Ops: AWS-native tools to keep close
Amazon DevOps Guru
Uses AI-ML to detect abnormal patterns in application operations and publish contextual insights on the same
Amazon Lookout for Metrics
Collates all data metrics across the landscape and analyzes them, predicting anomalies
Advance customer experience management with AI-enabled personalization
Amazon CodeGuru Reviewer
Analyzes source codes to detect possible malicious patterns, defects, and vulnerabilities
Amazon CodeGuru Profiler
Utilizes intelligent algorithms to analyze application performance and detect bottlenecks; helpful in maximizing performance at reduced costs
A fully managed AI-ML studio to build, train, and deploy machine learning models for business use cases or underlying operational necessities
Uses machine learning to analyze real-time video streams from IoT devices, automates environment anomaly detections, predictive maintenance, and safety monitoring
High-performance, AI-powered cloud data warehouse solution
A NoSQL database, flexible for storing and managing wide variety of data types, utilizes ML to automatically manage capacity and optimize performance
MySQL and PostgreSQL-compatible relational database solution leveraging AI-ML solutions to automatically tune DB parameters, scale capacity, and optimize performance
An intelligent, round the stack monitoring service
Operational and risk auditing, governance and compliance management of the AWS landscape
Fully managed intelligent service for data streaming from variety of sources including IoT devices, applications, platforms
Fully managed BI service utilized for automatic publishing of intuitive reports and dashboards
Transform Your AWS Management with Cloud4C SHOPTM
Echoing the autonomous vision, Cloud4C Self Healing Operations Platform (SHOPTM) combines dozens of operational landscapes, cloud platforms, and resources into a single pane of glass view for organizations, automatically governing migrations, modernizations, and managed operations at minimal human touch. An advanced Self Healing layer runs on top, monitoring the entire connected, multi-ecosystem stack 24/7 and predicting anomalies if any, patching errors even before they can cause a breach or outage. SHOP is behind Cloud4C's promise in delivering fully managed, risk- proofed hybrid and multi-cloud transformations, regardless of sector and platform, in a single high availability SLA from infra till application login. SHOPTM also integrates FinOps-as-a-Service tools to best manage cloud finances and maximize ROI of operations with time, guaranteeing utmost visibility into all workloads across ecosystems.
As an AWS Advanced Tier Services Partner and trusted AWS managed services provider in 26 countries with 600+ certified experts, Cloud4C deploys the advanced SHOPTM platform to render unique cloud evolution stories for businesses choosing AWS. Powered by AI-ML, automation technologies, and advanced data engines, firms can leverage the best of AWS cloud at maximum performance and returns, day in and day out. All mission-critical operations, running fully AWS-native or part privately or on third-party platforms, are brought under the monitoring mix to deliver organizations with complete observability of their AWS workloads. This saves the firm from regular evaluation or maintenance hassles, allowing timely modernization decisions and adopting cloud-native digital innovations to deliver next-gen services to customers.
Let us talk more if intelligent operational evolution seems like a future you would embrace.
Want to know about Amazon Rekognition? Here is a short video on Amazon Rekognition.