Cloud Diagrams now supports the following cloud resources:

• Pub/Sub topics & subscriptions.
• Google Kubernetes Engine (GKE) namespaces
• Google Cloud Firewall rules
• Google Cloud service accounts
• Google Cloud Filestore instances
• Google BigQuery datasets
• Amazon RDS Proxy
• Amazon RDS clusters

These additions give you a more complete view of your infrastructure, allowing you to spot dependencies and troubleshoot connections that were previously missing from your diagrams.

Here’s how you can start taking advantage of these newly-visible resources:

1. Google Cloud Pub/Sub: Visualize topics, subscriptions, and message flows between services and event triggers.
2. GKE Namespaces: Trace network paths between GKE Namespaces and Load Balancers to clearly understand traffic flow and service connectivity.
3. Google Cloud Firewall rules: Validate security boundaries and troubleshoot connectivity by visualizing how firewall rules allow or block traffic between instances and external services.
4. Google Cloud service accounts: Keep track of where your service accounts are assigned and what they have access to.
5. Google Cloud Filestore instances: Track storage connections to see which instances or clusters are mounted to your file shares.
6. BigQuery Datasets: Map data dependencies to clearly see which services and projects interact with your BQ datasets.  
7. RDS Proxy: Verify traffic routing between your applications and RDS instances via the intermediate proxy layer.
8. RDS Clusters: See the direct connections between your database nodes to understand your failover and scaling setup.

Open Cloud Diagrams to start seeing these new cloud resources in the context of your broader architecture.

Understanding cloud spend isn’t just about what you’re spending today, it’s about how that spend is changing over time.

Instead of running multiple reports with different time windows, you can now: 

• Compare spend and usage across two time periods in one view
• Identify trends and seasonality at a glance
• Quickly measure the impact of optimizations or configuration changes
• Spot unexpected increases earlier

With time period comparisons, you can define a primary and secondary time window in the same report. Instantly see total values, absolute change, and percent change, with visual highlights that draw attention to the largest increases and decreases. This makes it easier to understand what changed, how much it changed, and where to focus next.

To get started, open a new or existing report and add a secondary time window. 

For more details about time period comparisons, check out our Help documentation.

As your library of saved reports grows, quickly getting to the reports you use most can become a challenge. You shouldn’t have to search or scroll every time you want to answer a familiar question or access a frequent report. Now you don’t have to. 

You can now star your favorite reports in the DoiT Console and sort your report list to keep starred reports at the top. With just a few clicks, your most important reports are always front and center, exactly where you need them. Also, when you favorite a report, it’s starred for your user only. Other users won’t see or be affected by your starred reports.

This simple but powerful enhancement makes it easier to stay focused on the insights that matter most, while reducing friction in your day-to-day workflow. 

Work smarter with

• Faster access to the reports you rely on most
• Less friction when navigating large report libraries
• A more streamlined, personalized reporting workflow
• More time spent on insights, less time on navigation

Get started

• To favorite a report, select the star icon next the the report name on the report list
• To view starred reports, filter the reports list by “Favorite == yes”

For more details, consult our Help documentation or raise a support ticket.

Understanding cloud spend often means looking at more than one metric at a time, such as how cost relates to usage, list price, or savings.

You can now add multiple metrics, such as cost, usage, list price, and savings, to a single report. This makes it easier to validate data, reduce duplicate reporting, and deliver clearer insights without exporting or stitching together multiple views.

What this enables

• Compare cost, usage, and list price in one report
• Validate data more easily across metrics
• Reduce the need for duplicate or parallel reports
• Communicate insights more clearly to finance, engineering, and leadership
  
  

Getting started

• To add multiple metrics: open a new or existing report and select “+” next to Metrics

For more details, consult our Help documentation or raise a support ticket.

We’re excited to roll out a major upgrade to how DoiT helps you stay in control of your Google Cloud spend: real-time anomaly detection for Google BigQuery, including both on-demand and reservation workloads. Once enabled, you’ll receive alerts about unexpected BigQuery cost spikes in under an hour.

What’s new

Until now, anomaly insights for BigQuery relied on next-day billing-file ingestion. That meant if a bad query ran at 2 PM today, you wouldn’t know until tomorrow.

With our new real-time detection pipeline for BigQuery on-demand, we continuously ingest and analyze live BigQuery usage metadata, flag unusual usage patterns, and send you Slack or email alerts in less than an hour-not the next day.

Why it matters

Real-time detection for BigQuery means that you can:

• Catch runaway queries in minutes: Prevent accidental or inefficient queries from racking up costs before anyone notices.
• Protect against operational mistakes: Get alerted when abnormal query activity starts impacting spend.
• Strengthen your security posture: Real-time cost changes can signal unauthorized data access or compromised systems.

As DoiT’s BigQuery expert Sayle Matthews can attest, the risk of unchecked queries racking up significant costs in a short period of time is very high:

“One of the largest issues is seeing how much their bill is at any given moment and being able to alert them when a ‘runaway query’ hits. We have seen some examples where customers have single queries that cost $2,000 USD and run in less than a minute, and of course, these were run multiple times in quick succession. These mistakes lead to massive bills that aren't caught for days or weeks later.”

Watch this video for a more detailed breakdown of one such example of a runaway query that could have cost a customer thousands in unnecessary charges.

What you need to do

This feature is available for all DoiT customers with a paid Enhanced, Premium, or Enterprise subscription and a connected Google Cloud account. 

You can enable real-time anomaly detection for BigQuery when connecting a new project or editing an existing one. For a new project, take the following steps:

1. Sign in to the DoiT Cloud Intelligence console, select Integrate from the top navigation bar, and then select Google Cloud.
2. From the Connect drop-down, select Project.
3. Select the Real-time Anomalies – BigQuery checkbox. You can expand the feature to view its required permissions
4. Select Generate gcloud commands
5. Follow the instructions displayed in the side panel to configure your service account. See Connect a Google Cloud project for more information.
6. If the connection has been set up successfully, the status of the Real-time Anomalies – BigQuery feature will show Healthy.
   
   

To enable the feature on multiple projects, you'll need to repeat the process for each one. To add real-time anomalies to a connected project:

1. From the Integrate tab, select Google Cloud and find the project you want to enable it on.
2. Select the kebab menu (⋮) next to the project connection, and then select Edit.
3. Select the Real-time Anomalies – BigQuery checkbox to add the feature.
4. Select Generate gcloud commands.
5. Follow the instructions displayed in the side panel to update your custom role.
6. Select Done to enable the feature

Next steps

For more information about real-time anomaly detection, consult our Help documentation or raise a support ticket.

Data tells you what happened, but it doesn't always tell you why. We know that when you spot a cost anomaly or a usage spike in your cloud cost, usage or your business metrics, you need to capture that context immediately—before it’s lost in the shuffle of daily operations.

Starting today, you no longer need to navigate to a separate settings menu or lose your place in your analysis to leave a note. You can now create annotations directly from your reports by simply selecting a specific data point (using the right-click menu).

Manage custom metadata for your DoiT Cloud Intelligence™ resources with the new Labels API. Align governance objects, such as annotations, allocations, and reports, directly with your org structure, managed environments, cost centers, and other relevant entities.

Simple Taxonomy. Labels use single-value identifiers (like Production or Engineering) rather than complex key-value pairs. Filter and categorize resources faster with this flat structure.

Key Capabilities

• Centralized Management: Build a standard label library for your organization.
• Improve Governance: Label Annotations and Reports to properly classify them.
• Automate Workflows: Apply labels to new Reports or Annotations automatically during provisioning.

Supported Resources

• Annotations
• Allocations
• Reports
• Metric
• Budget
• Alert

API Reference

Google Cloud is updating its spend-based Committed Use Discount (CUD) program to a new data model that replaces credit-based offsets with direct discounted costs. 

In response, we have updated DoiT Cloud Analytics to fully support this new schema, ensuring your reporting remains accurate once Google Cloud automatically applies this change on existing spend-based CUDs beginning January 21, 2026.

This update simplifies billing by utilizing "Consumption Models" to represent discounted rates rather than applying separate credits to list prices. While your total costs will not increase, the structure of your billing data, and how CUD-related savings are displayed, will change.

What’s changing:

• CUD savings display: To align with Google’s new methodology, we are modifying how savings are displayed in Cloud Analytics Reports. Reports will shift from showing savings as an in-line calculation to a distinct savings presentation, reflecting the difference between on-demand prices and your final discounted cost
• Automatic SKU Conversion: Google Cloud will automatically convert your current CUD SKUs to the new ones. Consequently, any unique processing or presentation of your current SKUs within DoiT will be seamlessly transitioned to the new SKUs.

While this format is optional until Google applies it universally to all customers on January 21, 2026, you can opt into the new CUD format early via the Google Cloud console and start exploring your savings in DoiT Cloud Intelligence.

To learn more about the new CUD data model, submit a support ticket or reach out to your DoiT account team.

You use DoiT Cloud Intelligence™ to understand cloud spend and usage. The next step is making that insight repeatable and actionable in the systems where work actually happens: scripts, pipelines, and runbooks.

That's why we are introducing the DoiT Cloud Intelligence™ CLI, a straightforward way to interact with DoiT from your terminal and automate the work that keeps teams aligned and accountable.

With DoiT Cloud Intelligence CLI, you can:

• Shorter time from question to answer. Standardize recurring analyses and data pulls so stakeholders get consistent, up-to-date cloud cost reports without manual exports. 
• Reliable governance. Apply budgets, annotations, and allocation logic consistently across environments so ownership does not depend on one person remembering “the right way.”

For example, you can use Annotations directly from the CLI to capture the "why" behind the charts (deployments, migrations, incident response, policy changes), so anyone looking at a report later sees context immediately.

Practical examples:

• Create an annotation automatically when a production deployment completes, so cost deltas are clearly tied to releases.
• Add annotations when an incident is declared or resolved to connect reliability events to cost changes.
• Record business events (campaign launches, new customer onboardings) so spend is understood in business context, not just infrastructure terms.

Get started

If you can run a command in a terminal, you can get the value quickly. Install the CLI, authenticate, and then explore the available commands and actions. Docs and full command reference: https://help.doit.com/docs/cli

Start using this template by navigating to Operate -> CloudFlow -> Templates