GCP Lens provides a way for you to consistently measure your Google Cloud workloads against best practices and identify areas for improvement. The GCP Lens dashboard is automatically created when Google Cloud workloads are detected in your accounts and include the following information:

• Google Cloud Spend History w/ Forecast
• Breakdown by top Google Cloud services during last six months
• Breakdown by top Google Cloud projects during previous six months
• Map of your Google Cloud regions
• Coverage of eligible resources with CUDs for optimal cost

The information on the GCP Lens is updated every hour to bring the most up-to-date data to your fingertips. 

Committed use discounts (CUDs) for Cloud Run provide deeply discounted prices in exchange for committing to continuously use Cloud Run in a particular region for a one-year term [1].

Cloud Run committed use discounts automatically apply to all aggregated Cloud Run CPU, memory, and request usage in a region. Cloud Run committed use discounts do not apply to networking charges.

The new preset report 'Cloud Run CUD Eligible' makes it easy to understand how much eligible Cloud Run consumption exists. With this information, you can purchase Cloud Run CUDs with more confidence and achieve significant savings on your serverless workloads. 

[1] https://cloud.google.com/run/cud

You can filter the metrics used to build a report.  Previously we only allowed you to remove minor values.  However, with our new filters, you can support filters of any numeric amount.  This is great for focusing your data on only material cost and usage as well as eliminating outliers from trended analysis!

• Want to only see usage for services with spend > $500?  we got you!
• Want to remove costs below $50?  sure, no problem!
• Want to only see only services that have savings associated with them? easy!

We have released an enhancement to our reporting interface to 'Exclude partial intervals"

When reporting over any time interval (monthly, weekly, daily, etc.) the most current is always partial since that interval has not been completed.  This can be problematic for two common reports

• Comparative reports - when looking at % change the change from a completed month to an incomplete month is not relevant to drive decision making.  A common report would be
• Month over Month comparison (last 3 months, exclude partial). This will show the previous 3 months while hiding the current month.
• When comparing values its important to think about equivalence between intervals and we believe this should help here
• Row Heatmaps and Heatmap views - partial intervals skew heatmaps by introducing values that shift the highlighted scale dramatically.  Being able to exclude these values allows you to focus more clearly on signal and eliminate noise

Spot Scaling makes optimization recommendations for your Auto Scaling Groups (ASGs), ensuring that system uptime and EC2 Spot savings are both maximized.

What's New? Now you can adjust the Instance Types and Availability Zones in your recommendations!

Watch it in action below:

We are happy to announce two improvements to our Cloud Analytics Report configuration bar!

Daily Digest is a great way to stay on top of your cloud costs by receiving a daily email (or Slack message!) with a visual representation of your last day in the cloud. Daily Digests can cover all or a subset of your cloud usage by natively supporting attributions. 

You can configure Daily Digest directly from the Attributions list or from your Profile (under Notifications settings).

While the Pulse dashboard provides useful spend analysis information, sometimes it can be too overwhelming. Today, we are improving our Pulse dashboard by adding three summary cards at the top, making it easier to grasp the high-level spend pattern. 

• This month spend, including trend versus previous month
• This month forecast, including trend versus next month forecast
• 30-day anomaly cost, including comparison vs. the last month

The summary cards are interactive, meaning you can click the amount to drill down and get more context on what service is driving the cost (or forecast), along with the list of detected anomalies.

We are introducing a new preset custom metric GCE CUD Coverage to make it easy for our Google Cloud customers to gauge the utilization of the Google CUDs. This metric is built on top of two new preset attributions, - “GCP CUD Commitments” and “GCP Eligible for CUD”.

The “GCP CUD Commitments” attribution captures purchased Google Cloud Committed Use Discounts (CUDs) across all machine types and regions. The “GCP Eligible for CUD” attribution lists Google Cloud resources eligible for committed use discounts.

There also is a new preset report “GCP Compute CUD Coverage” displaying the metric and thus effectively rendering the CUD utilization as a heatmap. 

Amounts less than 100% mean that not all on-demand usage is covered by CUDs, more than 100% means that there are unused/underutilized CUDs.

We have improved the anomaly detection accuracy (and reducing the number of false-positive alerts) by automatically detecting seasonality (e.g. “spend patterns”) in your cloud usage and cost. In the attached examples, the suspected anomaly is a significant increase compared to previous days. However, our new forecasting model detects the cost is within the forecasted range, and the variation is due to historical trends and seasonal effects. 

Consider the following (real-life!) examples:

• the orange dot is the current daily cost which is the anomaly suspect
• the black dots represent historical data
• the blue line is our new forecasting model
• the blue region/band is the forecast range, i.e. upper/lower range of our prediction