When migrating to the cloud, organizations may underestimate the effort required to set up and manage cloud monitoring across deployments. Gaining visibility over cloud environments is complex enough even when there is only one cloud. In hybrid or multi-cloud environments, organizations can typically only view each cloud’s workloads separately, while it is critical to be able to view all cloud environments from a single pane of glass.
Below are there critical issues that might prevent your organization from gaining visibility over cloud workloads.
Limited Control Over Traffic to and From the Public Cloud
Moving workloads to the public cloud means losing many of the controls you had on-premises. Cloud providers do not grant customers direct access to shared infrastructure, and your traditional monitoring infrastructure will, in many cases, not work in the cloud.
If previously it was sufficient to use a network tap to mirror traffic and feed it into monitoring tools, in the cloud this is not an option. You also cannot deploy intrusion prevention systems (IPS) to filter traffic in real time. Basically, you cannot access data packets moving in the cloud and the information contained in them, which dramatically decreases visibility.
Organizations must pay attention to the data they are delivering to their monitoring tools. Cloud based resources can easily become "opaque containers" which are invisible to your monitoring infrastructure. This causes blind spots that may limit your ability to control security and performance.
Among the risks caused by monitoring blind spots are failure to alert when security incidents or breaches occur, compliance problems, unpredictable service disruption, and poor application performance.
Cloud providers provide log files that provide information about the activity of cloud workloads. You might think these logs can help you monitor for security and performance issues, because you can trigger alerts using log files.
The problem is that alerts are not enough—analysts or operations teams need to investigate those alerts, identify the root cause or threat and remediate it. These investigations typically require access to data packets—but cloud providers do not provide this level of data. Lack of packet data can also limit your ability to investigate the root cause of performance issues, in complex cloud environments.
How to Improve Cloud Visibility
Below are several ways technology and automation can help you improve cloud visibility.
Automated Risk Analysis
Log data in cloud environments is very difficult to work with, but can yield important insights about your environment. Leverage automated monitoring and security tools to:
Clean the data to remove noisy logs and identify relevant signals
Convert signals into meaningful alerts, and aggregate similar alerts
Use alerts to identify security or performance incidents and prioritize them
Augment data using external sources such as threat intelligence and internal sources such as asset management systems
This can give you an accurate, real-time analysis of the level of risk associated with your organization's unique IT environment.
Advanced Analytics Powered by AI and ML
One of the main challenges of cloud visibility is the variety of monitoring tools, each with a large number of event logs and performance indicators. Use a cloud monitoring solution that can collect and normalize these data sources, and perform advanced analytics using artificial intelligence and machine learning (AI/ML) techniques.
AI/ML can help increase the visibility of the cloud in several ways:
Historical data can be used to train algorithms, showing them a baseline of normal behavior
AI/ML algorithms can then automatically identify anomalies that might indicate security or performance issues in cloud services
The ability to automatically analyze huge volumes of data, helps derive insights across large, complex multi-cloud and hybrid-cloud deployments
Standardized Management and Automation
Many cloud operations are automated. However, when an automated task is performed on a large scale, it can become a barrier to visibility. Each team (security, operations, development) uses its own automation tools and scripts, making it difficult for the organization to get a unified view of the cloud.
It is important to standardize automation tools across the organization, and prefer tools that can orchestrate complex activities in a predictable way, using infrastructure as code. Use your automation platform to create playbooks, which define how cloud resources should work together to resolve a problem or achieve a goal.
Orchestration can improve cloud visibility in the following ways:
Enforcing company across cloud deployments, cloud provider accounts, and territories
Provide a self-service portal that can allow teams to deploy cloud resources with pre-approved, standardized configuration and deployment templates.
Create a single source of truth for all automated cloud activity.
Clean up your cloud environment by detecting and removing unneeded or non-standard resources
Automating Cloud Visibility with NetApp Cloud Insights
NetApp Cloud Insights is an infrastructure monitoring tool that gives you visibility into your complete infrastructure. With Cloud Insights, you can monitor, troubleshoot and optimize all your resources including your public clouds and your private data centers.
Cloud Insights helps you find problems fast before they impact your business. Optimize usage so you can defer spend, do more with your limited budgets, detect ransomware attacks before it’s too late and easily report on data access for security compliance auditing.
In particular, NetApp Cloud Insights helps you:
Discover your entire hybrid infrastructure, from the public cloud to the data center.
Create relevant dashboards instantly, or customize dashboards quickly to suit your needs.
Generate targeted, conditional alerts you can customize precisely.
Automatically build topologies, correlate metrics, detect greedy or degraded resources, and alert on anomalous user behavior.
Optimize cloud costs, saving money across your environment by identifying unused resources and right-sizing opportunities.
Gain an understanding of your Kubernetes architecture through topology visualization, and monitor health of Kubernetes clusters.
Protects cloud-based data from being misused by malicious or compromised users, through advanced machine learning and anomaly detection.