Strengthen Your Cloud Ops with Preventive Healing

The cloud is driving enterprise digital transformation. Gartner predicts that by 2026, public cloud spending will exceed 45% of all enterprise IT spending, a 2.5x growth from 2021. Enterprises globally are accelerating application modernization, embracing the cloud. This is giving rise to a few key trends.

Software-as-a-Service (SaaS) adoption is on the rise. So, organizations are using applications whose implementation/infrastructure they have little or no control over. Infrastructure-as-a-Service (IaaS), along with containerization and virtualization, is driving application deployment. This makes the cloud environment complex and made of thousands of moving parts connected by networks and APIs.

Moreover, for reasons of compliance and regulation, enterprises are creating regional and vertical cloud environments and data services. This adds to the complexity of multi-cloud environments.

DevOps and Agile teams are deploying to the cloud every day — even every hour. They need the infrastructure to be reliable and stable. Security risks are growing exponentially, demanding 100% coverage and preparedness. The cost of being reactive to a security breach could be prohibitive, so incidents need to be predicted and prevented.

The one outcome of all these emerging trends is that: Cloud operations are significantly more challenging than on-prem. In addition to preventing outages and network failures across complex and diverse environments, operations teams need to:

• Optimize cloud spend
• Minimize the need to hire large cloud teams
• Right-size resources
• Prevent over or under-provisioning
• Stop leaving resources idle

To do all this in a sustainable, scalable, and efficient manner, your cloud operations need AIOps. Here’s how AIOps can strengthen your cloud operations — preventatively and autonomously.

Real-time insight

You can’t solve a problem you can’t see. Especially across IaaS deployments, there can be thousands of containers connected via multiple APIs and networks. A minor outage in one of them can have significant downstream issues. To address this, enterprises choose monitoring to gain visibility into their cloud landscape. But this visibility can be overwhelming for Ops teams, who can’t keep an eye on everything. Some monitoring tools offer out-of-the-box dashboards. But they can be too generic to be useful.

On the other hand, AIOps can:

• Crunch all this information and offer insight into what’s important
• Offer dynamic discovery and visualization of application topologies, identifying weak points in real-time
• Build dashboards with customized KPIs unique to your organization
• Enable the C-suite to have a quick view of high-level metrics like revenue implications, downtimes averted, customer experience, etc.

While a good AIOps tool can and must offer these insights to help you make long-term plans for cloud optimization, this is just the beginning.

Improve CloudOps efficiency

Like we said above, monitoring collects vast amounts of data. But, it is humanly impossible for an IT team to process all this data to see trends manually. Even if your monitoring tool can identify anomalies and raise an alert, IT teams will not have the time to address all of them on any given day. Alert fatigue is counter-productive!

AIOps, with effective AI/ML models, can make sense of this data, suppress false alerts, predict incidents, and even perform root-cause analysis. This saves operations teams immense time and energy, improving their productivity and efficiency.

Optimize ROI

One of the biggest problems that leaders face is mounting cloud costs. In agile/DevOps teams, when any developer can spin up a virtual machine, idle resources can quickly get out of hand, adding to cloud costs. Enterprises set up real-time monitoring of usage and performance to prevent leaving resources idle. But that alone isn’t enough. Any monitoring solution that merely raises alerts for unused resources still relies on staff to turn them off.

AIOps can perform the remediation autonomously. For instance, an AIOps solution can track idle time, run tests to ensure that it’s an idle infra, and switch it off as appropriate.

Predict business-related incidents

Not all alerts are problems. More often than not, an anomaly can be the natural response to business events. For instance, your enterprise HR systems will see a spike on the day of the yearly review deadline. Likewise, an e-commerce website’s workload is going to be anomalous on Black Friday. Even within a day, some application workloads might fluctuate depending on how it’s being used.

A robust AIOps solution can correlate workload fluctuations to incidents and adjust provisioning accordingly. It can gradually increase provisioning based on usage trends as well as add/remove resources for one-off events.

Much of ITOps today is reactive — operations teams wait for problems to happen or outages to occur and then solve them. But with cloud environments, that is no longer acceptable. Even an outage for a few minutes can cause significant financial and reputational damage to brands. Cloud operations teams need to predict, prevent, and autonomously remediate incidents. AIOps is a proven way to achieve that.

About HEAL Software

HEAL Software is a renowned provider of AIOps (Artificial Intelligence for IT Operations) solutions. HEAL Software’s unwavering dedication to leveraging AI and automation empowers IT teams to address IT challenges, enhance incident management, reduce downtime, and ensure seamless IT operations. Through the analysis of extensive data, our solutions provide real-time insights, predictive analytics, and automated remediation, thereby enabling proactive monitoring and solution recommendation. Other features include anomaly detection, capacity forecasting, root cause analysis, and event correlation. With the state-of-the-art AIOps solutions, HEAL Software consistently drives digital transformation and delivers significant value to businesses across diverse industries.