GetEC2InstanceRecommendations Perl Example
use chilkat();
# This example requires the Chilkat API to have been previously unlocked.
# See Global Unlock Sample for sample code.
$rest = chilkat::CkRest->new();
$authAws = chilkat::CkAuthAws->new();
$authAws->put_AccessKey("AWS_ACCESS_KEY");
$authAws->put_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->put_Region("us-west-2");
$authAws->put_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 = $rest->Connect("compute-optimizer.us-west-2.amazonaws.com",443,1,1);
if ($success != 1) {
print "ConnectFailReason: " . $rest->get_ConnectFailReason() . "\r\n";
print $rest->lastErrorText() . "\r\n";
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 = chilkat::CkJsonObject->new();
$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 = chilkat::CkStringBuilder->new();
$json->EmitSb($sbRequestBody);
$sbResponseBody = chilkat::CkStringBuilder->new();
$success = $rest->FullRequestSb("POST","/",$sbRequestBody,$sbResponseBody);
if ($success != 1) {
print $rest->lastErrorText() . "\r\n";
exit;
}
$respStatusCode = $rest->get_ResponseStatusCode();
print "response status code = " . $respStatusCode . "\r\n";
if ($respStatusCode != 200) {
print "Response Header:" . "\r\n";
print $rest->responseHeader() . "\r\n";
print "Response Body:" . "\r\n";
print $sbResponseBody->getAsString() . "\r\n";
exit;
}
$jResp = chilkat::CkJsonObject->new();
$jResp->LoadSb($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 < $count_i) {
$jResp->put_I($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 < $count_i) {
$jResp->put_I($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 < $count_j) {
$jResp->put_J($j);
$strVal = $jResp->stringOf("instanceRecommendations[i].effectiveRecommendationPreferences.cpuVendorArchitectures[j]");
$j = $j + 1;
}
$j = 0;
$count_j = $jResp->SizeOfArray("instanceRecommendations[i].findingReasonCodes");
while ($j < $count_j) {
$jResp->put_J($j);
$strVal = $jResp->stringOf("instanceRecommendations[i].findingReasonCodes[j]");
$j = $j + 1;
}
$j = 0;
$count_j = $jResp->SizeOfArray("instanceRecommendations[i].inferredWorkloadTypes");
while ($j < $count_j) {
$jResp->put_J($j);
$strVal = $jResp->stringOf("instanceRecommendations[i].inferredWorkloadTypes[j]");
$j = $j + 1;
}
$j = 0;
$count_j = $jResp->SizeOfArray("instanceRecommendations[i].recommendationOptions");
while ($j < $count_j) {
$jResp->put_J($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 < $count_k) {
$jResp->put_K($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 < $count_k) {
$jResp->put_K($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 < $count_j) {
$jResp->put_J($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 < $count_j) {
$jResp->put_J($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"
# }
