Hybrid Cloud Operations with AIOps.

The last decade saw a great migration of enterprise workloads to cloud servers. Depending on the workload, enterprises choose either private, on-premise clouds or public cloud service providers. Among cloud buyers, 82% of enterprises have a Hybrid Cloud strategy(Flexera 2021 State of the Cloud Report). Enterprises prefer the advantage of greater control and security of the private cloud for their data centers and critical workloads. At the same time, they get the flexibility and scalability of public cloud for their general workloads. This has enabled a great level of dynamism without compromising on security or cost. However, this migration has not been without its difficulties.
Challenges in Hybrid Cloud Management
Hybrid cloud architectures often divide a single application across both private and public clouds. The workloads that require extremely low latency, complete control, and highest performance are typically stored on private clouds. On the other hand, the workloads without privacy or latency concerns that need to be scaled are typically on public clouds. So you could have an application front-end and related microservices on public cloud querying microservices that access the data center. The challenges now are obvious - ITOps is dealing with fragmented infrastructure communicating internally. The ITOps teams have to monitor the data center, internal microservices, hundreds or thousands of scalable, replicating microservices on the public cloud, and all associated API calls along with data passed in these APIs. Traditional alerts set on thresholds are frequently triggered but do not result in meaningful information. There are a high number of false positives. All these microservices have to be orchestrated and troubleshooting must be initiated fast in case of incidents. This is all too much to manage for ITOps teams. In the Cloud Security Alliance's Survey on Cloud challenges, 32% of respondents indicated that they do not have sufficient staff to manage cloud environments. They also cited network security and lack of cloud expertise as significant impediments. A lack of expertise is a recipe for problems. Indeed, misconfigurations and cloud issues are the primary causes of outages or security breaches, with outages lasting up to half a day. A single failure in a backbone router in the private cloud, for example, can cause outage in the entire cloud if it does not have a redundant backup. These issues persist despite using orchestration and configuration management tools. Moreover, while these tools can automate configurations, they cannot optimize them.
In addition, there are key governance challenges as well. With a fragmented IT infrastructure, managers and CIOs have a much harder time enforcing good governance and compliance practices - especially in the services in public clouds. In many cases, they do not have strong policies in place either. According to a survey by Cloud Security Alliance, budgetary concerns and lack of awareness were cited as the key reasons for not adopting better security practices. If this is the case for security, which is one of the most important priorities, we can expect that performance and efficiency practices will be just as weakly enforced. Moreover, management also has to balance the services deployed between private and public clouds in an optimized fashion to save costs. For e.g. if the private infrastructure can support more load it would be cost effective to run services from private cloud and expand to public for peak load periods. This requires foresight and accurate planning. All of these challenges make it harder to manage Hybrid Cloud deployments well.
AIOps for Hybrid Cloud
AIOps creates a new approach for ITOps to handle exactly these issues. Firstly, there's the observability. A single AIOps platform can integrate with all services on both clouds (public and private), collect all relevant KPIs, traces, and logs and make a truly single pane of glass observability solution. Moreover, this observability is more than just monitoring. It provides actionable insights when a service is behaving erroneously with KPI and Log Anomaly Detection. It gets to the bottom of an incident fast with Root Cause Analysis and also cuts down on the alert noise. This enables ITOps teams to cut down on outage lengths and keep a high level of availability. Secondly, there's the management and configuration itself. AIOps enables ITOps teams to create automated workflows that can be deployed to manage the entire IT infrastructure and services. It can orchestrate and automatically provision infrastructure and services across the private and public cloud. In the case of an incident, Incident Recognition identifies the root cause of the issue and creates an event. This event triggers an auto-remediation workflow that directly targets the associated root cause service to fix it. Finally, there's the governance and compliance aspect. An AIOps platform can use regularly scheduled workflows whose main purpose is to enforce adherence and find deviations from policy. It can also use AI optimization algorithms within a workflow model to distribute services between public and private cloud to create the most cost effective deployment that is also highly available.
The Algomox AIOps platforms are tailor-made to meet the needs of the modern enterprise - complete with the functionality to work with hybrid and multi cloud deployments, containers, and microservices. To learn more about Algomox AIOps, please visit  Algomox AIOps Platfrom Page.