Multi Cloud Dashboard

the cloud dashboard gives you a unified, real time view of your cloud infrastructure costs it’s designed to help it, engineering, and finance teams understand where money is being spent and make better decisions across aws, azure, gcp, other cloud providers and even on prem costs this dashboard is the first place users go after logging into the platform, and it serves as a powerful launch point for deep investigation whether you're trying to validate a charge, troubleshoot a cost spike, or simply understand trends over time, this page provides the visibility you need you can also get to the public cloud page by finding it on the left navigation list in the spend analytics section or by using https //ui amberflo io/it spend/cost analytics/overview what you can do from the public cloud dashboard, you can view your total cloud spend and begin to dissect it through a combination of filters, groupings, and time based comparisons it allows you to answer questions like how much did we spend on compute across all providers last week? are s3 storage costs trending upward month over month? which region is responsible for the spike in costs today? the dashboard supports exploration through flexible aggregation intervals and customizable time ranges you can start with a high level view and progressively drill down to finer detail, all within a single interface aggregation intervals understanding how to adjust time based settings is essential to making sense of your cloud cost data whether you’re tracking a short term cost spike, preparing a report for finance, or comparing trends over time, the dashboard allows you to tailor both the granularity of your data (aggregation) and the duration of time you’re analyzing (time range) this page explains how to use these controls effectively and when to choose different options based on your goal aggregation determines how cost data is grouped over time—whether by day, week, or month this controls the columns in your table and the intervals in your chart you can select from the following aggregation levels • daily ideal when you’re tracking recent activity or trying to pinpoint the exact day a cost spike occurred example you notice an unexpected rise in spend and want to isolate the exact day it began and what caused it • weekly best suited for trend analysis and identifying patterns across business units or projects example you’re comparing week over week compute spend to see if recent cost optimizations have taken effect • monthly useful for high level summaries, financial reporting, and monthly budget reviews example you’re preparing a month end report for finance and need a consolidated view of total cloud spend time range controls time range defines the start and end dates for the data you want to analyze this controls what data is visible in your chart and table available options include • month to date (default) provides a live view of current monthly spend example you want to check how you’re tracking against this month’s forecast or budget • past 7 days focuses on short term trends and recent cost anomalies example you’re troubleshooting a sudden increase in storage spend this week • past 30 days offers a medium term window ideal for comparing behavior across services or providers example you’re reviewing trends in your top three services over the past month • custom date range this allows complete flexibility where you can set your own start and end dates to analyze any specific period example you need to audit cloud spend during a product launch or investigate a billing anomaly from two months ago once you’ve selected your time range and aggregation level, the next step is to explore the cost data using grouping and filtering these controls allow you to dissect your spend from multiple angles, making it easier to pinpoint patterns and identify opportunities for optimization grouping how to break down the data grouping lets you restructure the data to see the various parts that make up your it spend amberflo provides the power to look at your costs in various levels of granularity when you group by a dimension you’re asking the dashboard to break down the total spend into parts, one for each value in that dimension for example grouping by cloud provider will show separate rows for aws, azure, and gcp grouping by service category will separate storage, compute, networking, and so on you can group by one or more dimensions simultaneously a common combination is grouping by cloud provider first and then by service category this allows you to see how compute spend is distributed across different clouds popular grouping dimensions include business unit service name service categories filtering narrowing the scope while grouping changes how the data is visualized, filtering changes what data is included in the first place filters help you focus on specific subsets of your cloud bill for example, you might filter to only include data from aws and gcp, or only look at services in the us east 1 region filters can be applied before or after groupings you can start by filtering to a single cloud provider, and then group by service to see how costs break down or group first, then apply filters to hone in on specific services or regions search within filters and groupings both grouping and filtering menus include a search box to help you quickly find the value you're looking for this is especially useful in large environments where the list of possible services, regions, or providers may be extensive search is case insensitive and updates results in real time as you type grouping and filtering can be combined in nearly unlimited ways each selection you make updates the chart and table in real time, helping you iterate quickly and stay focused on what matters the table view below the chart, you’ll find the table view, a powerful tool for analyzing your spend in greater detail this dynamic, interactive table uses the same filters, groupings, date range, and aggregation level you’ve set in the chart above, but displays the data in a structured, numerical format how to read the table each row in the table represents a unique value or combination of values based on your selected groupings for example, if you’ve grouped by service category and region, each row will display a specific category region pair the columns reflect your selected time interval, such as daily, weekly, or monthly this format makes it easy to track trends, compare costs across periods, and validate usage and spend at a granular level sorting and searching by default, the table is sorted to show the highest total cost at the top this helps you quickly identify the biggest contributors to your cloud bill you can also sort by any individual column click on the column header to sort ascending or descending based on that interval between the graph and the table you'll find a search bar you can type any term into this bar to filter the table rows in real time this is useful when you're looking for a specific service, region, or tag value within a large result set column totals and percentage differences each numeric column in the table includes a total value at the bottom this lets you see the sum of all listed items for that interval, essentially a subtotal filtered by your current selections the table also shows the percentage difference between columns, where applicable for example, if you're viewing weekly data, you can quickly identify which services or regions have grown or declined week over week this feature is especially helpful for trend spotting, anomaly detection, and verifying optimization efforts the table view complements the visual chart by offering a more precise, data rich format for validation, auditing, and reporting