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The latest News and Information on Cloud monitoring, security and related technologies.

Alerting on error log messages in Cloud SQL for SQL Server

With Cloud SQL for SQL Server, you can bring your existing SQL Server on-premises workloads to Google Cloud. Cloud SQL takes care of infrastructure, maintenance, and patching so you can focus on your application and users. A great way to take better care of your application is by monitoring the SQL Server error log for issues that may be affecting your users such as deadlocks, job failures, and changes in database health.

Introducing a high-usage tier for Managed Service for Prometheus

Prometheus is considered the de facto standard for Kubernetes application metrics, but running it yourself can strain engineering time and infrastructure resources when your usage grows. In March, we announced the general availability of Google Cloud Managed Service for Prometheus to help you offload that burden, and today, we’re excited to announce a new low-cost, high-usage pricing tier designed for customers who are moving large volumes of Kubernetes metrics over to the service.

When Legacy Systems Still Make Sense: The Role of Legacy Tech in Your Hybrid Digital Transformation

Despite all the attention cloud systems and enterprise cloud migrations receive, legacy software still plays an active role throughout enterprises. In many cases, critical business processes supported by legacy applications are just too crucial to core business functionality to risk migration.

Cloud SQL: Concepts of Networking

Cloud SQL provides a managed service for MySQL, PostgreSQL, and SQL Server databases as well as backups, high availability, maintenance, and so much more! In this episode of Networking End to End, Lorin Price discusses networking concepts from implementation and security to connectivity on Cloud SQL. Watch along to learn about the options for deploying Cloud SQL and tips on how to determine who and what can access your Cloud SQL instance.

Top 5 AWS Services Every Developer Should know

AWS is a beast in cloud services and has more than 200+ services. It is not easy for a novice user to select the services that fit his need. Even after selecting the right service, you need to make sure you use it the right way because each service has many different variants. In this article, we will guide you about the top 5 most frequently used AWS services which every developer must know.

New observability features for your Splunk Dataflow streaming pipelines

We’re thrilled to announce several new observability features for the Pub/Sub to Splunk Dataflow template to help operators keep a tab on their streaming pipeline performance. Splunk Enterprise and Splunk Cloud customers use the Splunk Dataflow template to reliably export Google Cloud logs for in-depth analytics for security, IT or business use cases.

Cloud computing powers the world's financial exchanges

Embracing the cloud is not just a case of improving infrastructure, experts believe, but also a way to drive transformation. Many of the world’s largest financial exchanges are transforming the way they run global capital markets through the adoption of cloud computing technologies. In November, financial derivatives exchange CME Group entered a 10-year partnership with Google that will move CME’s IT infrastructure and markets to the cloud.

5 Common Amazon SQS Issues

The simple query service (SQS) was one of the first services AWS offered. It’s a managed queuing service that lets you take pressure from your downstream services. You put your items on the queue, and other services can pull them whenever they have the capacity to work on them. It’s a managed service, so you don’t have to install or maintain the software yourself; you just configure a queue and start pushing to and pulling from it. So SQS is very simple to get started with.

Data Lake vs Data Warehouse: What's the Difference?

Although both data lakes and data warehouses are commonly used to store large amounts of data, the phrases are not interchangeable. A data lake is not a straight substitute for a data warehouse; rather, they are complementary technologies that serve a variety of use cases, some of which overlap. Most companies that have a data lake also have a data warehouse. The two methods of data storage are sometimes mistaken, yet they are vastly different.