GetEC2InstanceRecommendations unicodeCpp Example
#include <CkRestW.h>
#include <CkAuthAwsW.h>
#include <CkJsonObjectW.h>
#include <CkStringBuilderW.h>
void ChilkatSample(void)
{
// This example requires the Chilkat API to have been previously unlocked.
// See Global Unlock Sample for sample code.
CkRestW rest;
bool success;
CkAuthAwsW authAws;
authAws.put_AccessKey(L"AWS_ACCESS_KEY");
authAws.put_SecretKey(L"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(L"us-west-2");
authAws.put_ServiceName(L"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(L"compute-optimizer.us-west-2.amazonaws.com",443,true,true);
if (success != true) {
wprintf(L"ConnectFailReason: %d\n",rest.get_ConnectFailReason());
wprintf(L"%s\n",rest.lastErrorText());
return;
}
// 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
CkJsonObjectW json;
json.UpdateString(L"accountIds[0]",L"string");
json.UpdateString(L"filters[0].name",L"string");
json.UpdateString(L"filters[0].values[0]",L"string");
json.UpdateString(L"instanceArns[0]",L"string");
json.UpdateInt(L"maxResults",123);
json.UpdateString(L"nextToken",L"string");
json.UpdateString(L"recommendationPreferences.cpuVendorArchitectures[0]",L"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(L"Content-Type",L"application/x-amz-json-1.0");
rest.AddHeader(L"X-Amz-Target",L"ComputeOptimizerService.GetEC2InstanceRecommendations");
CkStringBuilderW sbRequestBody;
json.EmitSb(sbRequestBody);
CkStringBuilderW sbResponseBody;
success = rest.FullRequestSb(L"POST",L"/",sbRequestBody,sbResponseBody);
if (success != true) {
wprintf(L"%s\n",rest.lastErrorText());
return;
}
int respStatusCode = rest.get_ResponseStatusCode();
wprintf(L"response status code = %d\n",respStatusCode);
if (respStatusCode != 200) {
wprintf(L"Response Header:\n");
wprintf(L"%s\n",rest.responseHeader());
wprintf(L"Response Body:\n");
wprintf(L"%s\n",sbResponseBody.getAsString());
return;
}
CkJsonObjectW jResp;
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
// Chilkat functions returning "const char *" return a pointer to temporary internal memory owned and managed by Chilkat.
// See this example explaining how this memory should be used: const char * functions.
const wchar_t *code = 0;
const wchar_t *identifier = 0;
const wchar_t *message = 0;
const wchar_t *accountId = 0;
const wchar_t *currentInstanceType = 0;
const wchar_t *currentPerformanceRisk = 0;
const wchar_t *EnhancedInfrastructureMetrics = 0;
const wchar_t *InferredWorkloadTypes = 0;
const wchar_t *finding = 0;
const wchar_t *instanceArn = 0;
const wchar_t *instanceName = 0;
int lastRefreshTimestamp;
int lookBackPeriodInDays;
int j;
int count_j;
const wchar_t *strVal = 0;
const wchar_t *instanceType = 0;
const wchar_t *migrationEffort = 0;
int performanceRisk;
int rank;
const wchar_t *v_Currency = 0;
int Value;
int SavingsOpportunityPercentage;
int k;
int count_k;
const wchar_t *name = 0;
const wchar_t *statistic = 0;
int value;
const wchar_t *recommendationSourceArn = 0;
const wchar_t *recommendationSourceType = 0;
const wchar_t *nextToken = jResp.stringOf(L"nextToken");
int i = 0;
int count_i = jResp.SizeOfArray(L"errors");
while (i < count_i) {
jResp.put_I(i);
code = jResp.stringOf(L"errors[i].code");
identifier = jResp.stringOf(L"errors[i].identifier");
message = jResp.stringOf(L"errors[i].message");
i = i + 1;
}
i = 0;
count_i = jResp.SizeOfArray(L"instanceRecommendations");
while (i < count_i) {
jResp.put_I(i);
accountId = jResp.stringOf(L"instanceRecommendations[i].accountId");
currentInstanceType = jResp.stringOf(L"instanceRecommendations[i].currentInstanceType");
currentPerformanceRisk = jResp.stringOf(L"instanceRecommendations[i].currentPerformanceRisk");
EnhancedInfrastructureMetrics = jResp.stringOf(L"instanceRecommendations[i].effectiveRecommendationPreferences.enhancedInfrastructureMetrics");
InferredWorkloadTypes = jResp.stringOf(L"instanceRecommendations[i].effectiveRecommendationPreferences.inferredWorkloadTypes");
finding = jResp.stringOf(L"instanceRecommendations[i].finding");
instanceArn = jResp.stringOf(L"instanceRecommendations[i].instanceArn");
instanceName = jResp.stringOf(L"instanceRecommendations[i].instanceName");
lastRefreshTimestamp = jResp.IntOf(L"instanceRecommendations[i].lastRefreshTimestamp");
lookBackPeriodInDays = jResp.IntOf(L"instanceRecommendations[i].lookBackPeriodInDays");
j = 0;
count_j = jResp.SizeOfArray(L"instanceRecommendations[i].effectiveRecommendationPreferences.cpuVendorArchitectures");
while (j < count_j) {
jResp.put_J(j);
strVal = jResp.stringOf(L"instanceRecommendations[i].effectiveRecommendationPreferences.cpuVendorArchitectures[j]");
j = j + 1;
}
j = 0;
count_j = jResp.SizeOfArray(L"instanceRecommendations[i].findingReasonCodes");
while (j < count_j) {
jResp.put_J(j);
strVal = jResp.stringOf(L"instanceRecommendations[i].findingReasonCodes[j]");
j = j + 1;
}
j = 0;
count_j = jResp.SizeOfArray(L"instanceRecommendations[i].inferredWorkloadTypes");
while (j < count_j) {
jResp.put_J(j);
strVal = jResp.stringOf(L"instanceRecommendations[i].inferredWorkloadTypes[j]");
j = j + 1;
}
j = 0;
count_j = jResp.SizeOfArray(L"instanceRecommendations[i].recommendationOptions");
while (j < count_j) {
jResp.put_J(j);
instanceType = jResp.stringOf(L"instanceRecommendations[i].recommendationOptions[j].instanceType");
migrationEffort = jResp.stringOf(L"instanceRecommendations[i].recommendationOptions[j].migrationEffort");
performanceRisk = jResp.IntOf(L"instanceRecommendations[i].recommendationOptions[j].performanceRisk");
rank = jResp.IntOf(L"instanceRecommendations[i].recommendationOptions[j].rank");
v_Currency = jResp.stringOf(L"instanceRecommendations[i].recommendationOptions[j].savingsOpportunity.estimatedMonthlySavings.currency");
Value = jResp.IntOf(L"instanceRecommendations[i].recommendationOptions[j].savingsOpportunity.estimatedMonthlySavings.value");
SavingsOpportunityPercentage = jResp.IntOf(L"instanceRecommendations[i].recommendationOptions[j].savingsOpportunity.savingsOpportunityPercentage");
k = 0;
count_k = jResp.SizeOfArray(L"instanceRecommendations[i].recommendationOptions[j].platformDifferences");
while (k < count_k) {
jResp.put_K(k);
strVal = jResp.stringOf(L"instanceRecommendations[i].recommendationOptions[j].platformDifferences[k]");
k = k + 1;
}
k = 0;
count_k = jResp.SizeOfArray(L"instanceRecommendations[i].recommendationOptions[j].projectedUtilizationMetrics");
while (k < count_k) {
jResp.put_K(k);
name = jResp.stringOf(L"instanceRecommendations[i].recommendationOptions[j].projectedUtilizationMetrics[k].name");
statistic = jResp.stringOf(L"instanceRecommendations[i].recommendationOptions[j].projectedUtilizationMetrics[k].statistic");
value = jResp.IntOf(L"instanceRecommendations[i].recommendationOptions[j].projectedUtilizationMetrics[k].value");
k = k + 1;
}
j = j + 1;
}
j = 0;
count_j = jResp.SizeOfArray(L"instanceRecommendations[i].recommendationSources");
while (j < count_j) {
jResp.put_J(j);
recommendationSourceArn = jResp.stringOf(L"instanceRecommendations[i].recommendationSources[j].recommendationSourceArn");
recommendationSourceType = jResp.stringOf(L"instanceRecommendations[i].recommendationSources[j].recommendationSourceType");
j = j + 1;
}
j = 0;
count_j = jResp.SizeOfArray(L"instanceRecommendations[i].utilizationMetrics");
while (j < count_j) {
jResp.put_J(j);
name = jResp.stringOf(L"instanceRecommendations[i].utilizationMetrics[j].name");
statistic = jResp.stringOf(L"instanceRecommendations[i].utilizationMetrics[j].statistic");
value = jResp.IntOf(L"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"
// }
}
