GetEC2InstanceRecommendations Powershell Example
Add-Type -Path "C:\chilkat\ChilkatDotNet47-9.5.0-x64\ChilkatDotNet47.dll"
# This example requires the Chilkat API to have been previously unlocked.
# See Global Unlock Sample for sample code.
$rest = New-Object Chilkat.Rest
$authAws = New-Object Chilkat.AuthAws
$authAws.AccessKey = "AWS_ACCESS_KEY"
$authAws.SecretKey = "AWS_SECRET_KEY"
# Don't forget to change the region to your particular region. (Also make the same change in the call to Connect below.)
$authAws.Region = "us-west-2"
$authAws.ServiceName = "compute-optimizer"
# SetAuthAws causes Chilkat to automatically add the following headers: Authorization, X-Amz-Date
$rest.SetAuthAws($authAws)
# URL: https://compute-optimizer.us-west-2.amazonaws.com/
# Use the same region as specified above.
$success = $rest.Connect("compute-optimizer.us-west-2.amazonaws.com",443,$true,$true)
if ($success -ne $true) {
$("ConnectFailReason: " + $rest.ConnectFailReason)
$($rest.LastErrorText)
exit
}
# The following code creates the JSON request body.
# The JSON created by this code is shown below.
# Use this online tool to generate code from sample JSON:
# Generate Code to Create JSON
$json = New-Object Chilkat.JsonObject
$json.UpdateString("accountIds[0]","string")
$json.UpdateString("filters[0].name","string")
$json.UpdateString("filters[0].values[0]","string")
$json.UpdateString("instanceArns[0]","string")
$json.UpdateInt("maxResults",123)
$json.UpdateString("nextToken","string")
$json.UpdateString("recommendationPreferences.cpuVendorArchitectures[0]","string")
# The JSON request body created by the above code:
# {
# "accountIds": [
# "string"
# ],
# "filters": [
# {
# "name": "string",
# "values": [
# "string"
# ]
# }
# ],
# "instanceArns": [
# "string"
# ],
# "maxResults": number,
# "nextToken": "string",
# "recommendationPreferences": {
# "cpuVendorArchitectures": [
# "string"
# ]
# }
# }
$rest.AddHeader("Content-Type","application/x-amz-json-1.0")
$rest.AddHeader("X-Amz-Target","ComputeOptimizerService.GetEC2InstanceRecommendations")
$sbRequestBody = New-Object Chilkat.StringBuilder
$json.EmitSb($sbRequestBody)
$sbResponseBody = New-Object Chilkat.StringBuilder
$success = $rest.FullRequestSb("POST","/",$sbRequestBody,$sbResponseBody)
if ($success -ne $true) {
$($rest.LastErrorText)
exit
}
$respStatusCode = $rest.ResponseStatusCode
$("response status code = " + $respStatusCode)
if ($respStatusCode -ne 200) {
$("Response Header:")
$($rest.ResponseHeader)
$("Response Body:")
$($sbResponseBody.GetAsString())
exit
}
$jResp = New-Object Chilkat.JsonObject
$jResp.LoadSb($sbResponseBody)
# The following code parses the JSON response.
# A sample JSON response is shown below the sample code.
# Use this online tool to generate parsing code from sample JSON:
# Generate Parsing Code from JSON
$nextToken = $jResp.StringOf("nextToken")
$i = 0
$count_i = $jResp.SizeOfArray("errors")
while ($i -lt $count_i) {
$jResp.I = $i
$code = $jResp.StringOf("errors[i].code")
$identifier = $jResp.StringOf("errors[i].identifier")
$message = $jResp.StringOf("errors[i].message")
$i = $i + 1
}
$i = 0
$count_i = $jResp.SizeOfArray("instanceRecommendations")
while ($i -lt $count_i) {
$jResp.I = $i
$accountId = $jResp.StringOf("instanceRecommendations[i].accountId")
$currentInstanceType = $jResp.StringOf("instanceRecommendations[i].currentInstanceType")
$currentPerformanceRisk = $jResp.StringOf("instanceRecommendations[i].currentPerformanceRisk")
$EnhancedInfrastructureMetrics = $jResp.StringOf("instanceRecommendations[i].effectiveRecommendationPreferences.enhancedInfrastructureMetrics")
$InferredWorkloadTypes = $jResp.StringOf("instanceRecommendations[i].effectiveRecommendationPreferences.inferredWorkloadTypes")
$finding = $jResp.StringOf("instanceRecommendations[i].finding")
$instanceArn = $jResp.StringOf("instanceRecommendations[i].instanceArn")
$instanceName = $jResp.StringOf("instanceRecommendations[i].instanceName")
$lastRefreshTimestamp = $jResp.IntOf("instanceRecommendations[i].lastRefreshTimestamp")
$lookBackPeriodInDays = $jResp.IntOf("instanceRecommendations[i].lookBackPeriodInDays")
$j = 0
$count_j = $jResp.SizeOfArray("instanceRecommendations[i].effectiveRecommendationPreferences.cpuVendorArchitectures")
while ($j -lt $count_j) {
$jResp.J = $j
$strVal = $jResp.StringOf("instanceRecommendations[i].effectiveRecommendationPreferences.cpuVendorArchitectures[j]")
$j = $j + 1
}
$j = 0
$count_j = $jResp.SizeOfArray("instanceRecommendations[i].findingReasonCodes")
while ($j -lt $count_j) {
$jResp.J = $j
$strVal = $jResp.StringOf("instanceRecommendations[i].findingReasonCodes[j]")
$j = $j + 1
}
$j = 0
$count_j = $jResp.SizeOfArray("instanceRecommendations[i].inferredWorkloadTypes")
while ($j -lt $count_j) {
$jResp.J = $j
$strVal = $jResp.StringOf("instanceRecommendations[i].inferredWorkloadTypes[j]")
$j = $j + 1
}
$j = 0
$count_j = $jResp.SizeOfArray("instanceRecommendations[i].recommendationOptions")
while ($j -lt $count_j) {
$jResp.J = $j
$instanceType = $jResp.StringOf("instanceRecommendations[i].recommendationOptions[j].instanceType")
$migrationEffort = $jResp.StringOf("instanceRecommendations[i].recommendationOptions[j].migrationEffort")
$performanceRisk = $jResp.IntOf("instanceRecommendations[i].recommendationOptions[j].performanceRisk")
$rank = $jResp.IntOf("instanceRecommendations[i].recommendationOptions[j].rank")
$v_Currency = $jResp.StringOf("instanceRecommendations[i].recommendationOptions[j].savingsOpportunity.estimatedMonthlySavings.currency")
$Value = $jResp.IntOf("instanceRecommendations[i].recommendationOptions[j].savingsOpportunity.estimatedMonthlySavings.value")
$SavingsOpportunityPercentage = $jResp.IntOf("instanceRecommendations[i].recommendationOptions[j].savingsOpportunity.savingsOpportunityPercentage")
$k = 0
$count_k = $jResp.SizeOfArray("instanceRecommendations[i].recommendationOptions[j].platformDifferences")
while ($k -lt $count_k) {
$jResp.K = $k
$strVal = $jResp.StringOf("instanceRecommendations[i].recommendationOptions[j].platformDifferences[k]")
$k = $k + 1
}
$k = 0
$count_k = $jResp.SizeOfArray("instanceRecommendations[i].recommendationOptions[j].projectedUtilizationMetrics")
while ($k -lt $count_k) {
$jResp.K = $k
$name = $jResp.StringOf("instanceRecommendations[i].recommendationOptions[j].projectedUtilizationMetrics[k].name")
$statistic = $jResp.StringOf("instanceRecommendations[i].recommendationOptions[j].projectedUtilizationMetrics[k].statistic")
$value = $jResp.IntOf("instanceRecommendations[i].recommendationOptions[j].projectedUtilizationMetrics[k].value")
$k = $k + 1
}
$j = $j + 1
}
$j = 0
$count_j = $jResp.SizeOfArray("instanceRecommendations[i].recommendationSources")
while ($j -lt $count_j) {
$jResp.J = $j
$recommendationSourceArn = $jResp.StringOf("instanceRecommendations[i].recommendationSources[j].recommendationSourceArn")
$recommendationSourceType = $jResp.StringOf("instanceRecommendations[i].recommendationSources[j].recommendationSourceType")
$j = $j + 1
}
$j = 0
$count_j = $jResp.SizeOfArray("instanceRecommendations[i].utilizationMetrics")
while ($j -lt $count_j) {
$jResp.J = $j
$name = $jResp.StringOf("instanceRecommendations[i].utilizationMetrics[j].name")
$statistic = $jResp.StringOf("instanceRecommendations[i].utilizationMetrics[j].statistic")
$value = $jResp.IntOf("instanceRecommendations[i].utilizationMetrics[j].value")
$j = $j + 1
}
$i = $i + 1
}
# A sample JSON response body parsed by the above code:
# {
# "errors": [
# {
# "code": "string",
# "identifier": "string",
# "message": "string"
# }
# ],
# "instanceRecommendations": [
# {
# "accountId": "string",
# "currentInstanceType": "string",
# "currentPerformanceRisk": "string",
# "effectiveRecommendationPreferences": {
# "cpuVendorArchitectures": [
# "string"
# ],
# "enhancedInfrastructureMetrics": "string",
# "inferredWorkloadTypes": "string"
# },
# "finding": "string",
# "findingReasonCodes": [
# "string"
# ],
# "inferredWorkloadTypes": [
# "string"
# ],
# "instanceArn": "string",
# "instanceName": "string",
# "lastRefreshTimestamp": number,
# "lookBackPeriodInDays": number,
# "recommendationOptions": [
# {
# "instanceType": "string",
# "migrationEffort": "string",
# "performanceRisk": number,
# "platformDifferences": [
# "string"
# ],
# "projectedUtilizationMetrics": [
# {
# "name": "string",
# "statistic": "string",
# "value": number
# }
# ],
# "rank": number,
# "savingsOpportunity": {
# "estimatedMonthlySavings": {
# "currency": "string",
# "value": number
# },
# "savingsOpportunityPercentage": number
# }
# }
# ],
# "recommendationSources": [
# {
# "recommendationSourceArn": "string",
# "recommendationSourceType": "string"
# }
# ],
# "utilizationMetrics": [
# {
# "name": "string",
# "statistic": "string",
# "value": number
# }
# ]
# }
# ],
# "nextToken": "string"
# }
