While enterprise IT teams adapt server deployments to local, cloud, or hybrid models, there are many administrative challenges. To overcome these IT management challenges, organizations are now using discrete solutions to meet their individual management needs. However, customers can leverage the cloud-scale infrastructure to increase ease of deployment with unified “IT management as a service” called Microsoft Operations Management Suite (OMS). Management functions such as monitoring, backup and automation are provided as a service from the cloud, connecting all servers in all environments (onsite, Azure, other clouds such as AWS), and IT staff centrally manage operations WHO is composed of the following four modules.
Gain visibility across your Hybrid Enterprise Cloud.
Orchestrate complex and repetitive operations.
Increase data protection and application availability
Help secure your workloads, servers, and users
Gaining Operational Insights
Today, traditional computing typically uses several different tools for monitoring platforms and applications, network monitoring, and security analysis. Extending these tools to the cloud is difficult in many ways, including connectivity, agility, and the volume of data. In addition, there is an increasing need to analyze and combine operational information from various sources. With OMS Log Analytics, organizations can collect, store, and analyze log data from virtually any Windows Server and Linux source for unparalleled data center and cloud information, including Azure and AWS.
Start using Log Analytics
Log Analytics is new to most businesses, so a brief introduction can help you. To start Log Analytics, you must perform the following steps:
The first step is to deploy the OMS workspace in the Azure portal. This allows you to choose from different editions that define the volume and retention of data. Then select the solution to use. A solution is a set of logic, visualization, and data acquisition rules that address the key customer challenges. More in-depth information to investigate and resolve operational issues more quickly, collect and correlate different types of machine data, and actively engage in activities such as change tracking, patch status reports, and security audits.
Afterward you are connecting your servers to Log Analytics by deploying the Windows or Linux agent on your machines. For Azure virtual machines it is an automated process; for virtual machines in other clouds or on-premises it could be done by downloading and installing the agent or by using automation tools therefore. The connectivity between the agent and Log Analytics is established by using outbound Internet connectivity with or without a proxy. Thus there is no need to open any on-premises firewalls for establishing inbound connectivity.
For machines that can not connect to the Internet, you can use the Log Analytics Forwarder (Gateway) being previewed. With OMS Log Analytics Forwarder, you can access the Internet and send data to an internal central server that acts as an http forwarding proxy. This allows you to collect log files from any machine on the network without the need for Internet access. In addition, logs stored from other Azure services in your Azure storage account can be retrieved and included in the repository. Then, define the data to collect from the virtual machine. You can add any Windows event log, Windows performance counter, Linux performance counter, IIS log, custom field, custom log, and syslog. All of these log files are transferred with low latency and stored in a central repository for further analysis. You can add user accounts to OMS RBAC log analysis to define detailed access for various users and user groups.
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